Hackers are now using botnets to automate Google searches on a massive scale, generating over 80,000 queries daily. By distributing searches across many compromised machines, hackers can evade detection techniques used by search engines. Hackers first obtain a botnet, then use a tool to coordinate widespread searching using lists of search terms likely to return vulnerable sites. This enables hackers to efficiently collect many potential targets for crafting attacks.
Android mobile platform security and malware surveyeSAT Journals
Abstract As mobile devices become ubiquitous, more people and companies are readily adopting the technology to conduct day-to-day business, and are increasing the amount of personal data transmitted and stored on these devices. These devices are now part of a global infrastructure powering communication and how we do business around the world. In turn, the inherent vulnerabilities are becoming an ever more critical topic of interest and challenge as we continue to see a rapid rate of malware development. This paper is a comprehensive survey on a broad view of the growing Android community, its rapidly growing malware attacks, and security concerns. Serving to aid in the continuous challenge of identifying current and future vulnerabilities as well as incorporating security strategies against them, this survey will focus primarily on mobile devices (also known as smart phones) running the Android mobile operating system between the years of 2007 and 2013. Index Terms: mobile, Android, malware, security
Analyzing the effectualness of Phishing Algorithms in Web Applications Inques...Editor IJMTER
The initial and proficient loss of deception is belief. A wolf in sheep’s clothing is tough
to recognize, similar is the schema of a phishing website. Phishing is the emulsion of social
engineering and technical exploits designed to persuade a victim to provide personal information, for
the fiscal gain of the attacker. It is a new kind of network assault where the attacker creates a spitting
image of an already existing Web Page to delude users. In this paper, we will study two anti-phishing
algorithms, one an end-host based algorithm known as the LinkGuard Algorithm, while the other a
content based approach known as the CANTINA.
Create an Artificially Intelligent (AI) Computer virus , which can modify its signature to avoid detection from an Anti Virus software.
A computer virus which can stop all its infectious activities and go into the state of incubation when a full system scan is going on through an Anti Virus scan. What is the possibility of seeing such computer viruses in near future?
This document provides an introduction to ethical hacking. It discusses what ethical hacking is, the types of hackers (white hat, black hat, grey hat, suicide hacker), types of hacking (website, network, email, password, computer), phases of ethical hacking (reconnaissance, scanning, gaining access, maintaining access, clearing tracks, reporting), footprinting (gathering information about a target system), and fingerprinting (determining the operating system of a target). Ethical hacking involves finding vulnerabilities in a system with permission in order to fix them, while illegal hacking involves exploiting vulnerabilities for malicious purposes without permission.
Clustering Categorical Data for Internet Security ApplicationsIJSTA
This document summarizes research on clustering categorical data for internet security applications. It discusses using clustering techniques for malware categorization, phishing website detection, and detecting secure emails. Feature extraction and categorization are generally used to automatically group file samples or websites. The document also reviews several related works applying clustering and other techniques for malware analysis, phishing detection, and analyzing privacy-breaching malware behavior.
Today's security is that the main downside and every one the work is finished over the net mistreatment knowledge. whereas the information is out there, there square measure many varieties of users who act with knowledge and a few of them for his or her would like it all for his or her gaining data. There square measure numerous techniques used for cover of information however the hacker or cracker is a lot of intelligent to hack the security, there square measure 2 classes of hackers theyre completely different from one another on the idea of their arrange. The one who has smart plans square measure referred to as moral hackers as a result of the ethics to use their talent and techniques of hacking to supply security to the organization. this idea describes concerning the hacking, styles of hackers, rules of moral hacking and also the blessings of the moral hacking. Mukesh. M | Dr. S. Vengateshkumar "Ethical Hacking" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29351.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/29351/ethical-hacking/mukesh-m
This document presents a proposed machine learning-based Android malware detection system. It discusses how Android devices are increasingly being targeted by malware due to the open nature of the Android app marketplace. The proposed system would use machine learning classifiers to analyze permission-based features and events from Android apps to classify them as goodware or malware. It would monitor apps and detect malware to enhance security and privacy for smartphone users. The system design uses k-means clustering and naive Bayes classification on XML and DEX file features to detect malware in two layers if needed.
Android mobile platform security and malware surveyeSAT Journals
Abstract As mobile devices become ubiquitous, more people and companies are readily adopting the technology to conduct day-to-day business, and are increasing the amount of personal data transmitted and stored on these devices. These devices are now part of a global infrastructure powering communication and how we do business around the world. In turn, the inherent vulnerabilities are becoming an ever more critical topic of interest and challenge as we continue to see a rapid rate of malware development. This paper is a comprehensive survey on a broad view of the growing Android community, its rapidly growing malware attacks, and security concerns. Serving to aid in the continuous challenge of identifying current and future vulnerabilities as well as incorporating security strategies against them, this survey will focus primarily on mobile devices (also known as smart phones) running the Android mobile operating system between the years of 2007 and 2013. Index Terms: mobile, Android, malware, security
Analyzing the effectualness of Phishing Algorithms in Web Applications Inques...Editor IJMTER
The initial and proficient loss of deception is belief. A wolf in sheep’s clothing is tough
to recognize, similar is the schema of a phishing website. Phishing is the emulsion of social
engineering and technical exploits designed to persuade a victim to provide personal information, for
the fiscal gain of the attacker. It is a new kind of network assault where the attacker creates a spitting
image of an already existing Web Page to delude users. In this paper, we will study two anti-phishing
algorithms, one an end-host based algorithm known as the LinkGuard Algorithm, while the other a
content based approach known as the CANTINA.
Create an Artificially Intelligent (AI) Computer virus , which can modify its signature to avoid detection from an Anti Virus software.
A computer virus which can stop all its infectious activities and go into the state of incubation when a full system scan is going on through an Anti Virus scan. What is the possibility of seeing such computer viruses in near future?
This document provides an introduction to ethical hacking. It discusses what ethical hacking is, the types of hackers (white hat, black hat, grey hat, suicide hacker), types of hacking (website, network, email, password, computer), phases of ethical hacking (reconnaissance, scanning, gaining access, maintaining access, clearing tracks, reporting), footprinting (gathering information about a target system), and fingerprinting (determining the operating system of a target). Ethical hacking involves finding vulnerabilities in a system with permission in order to fix them, while illegal hacking involves exploiting vulnerabilities for malicious purposes without permission.
Clustering Categorical Data for Internet Security ApplicationsIJSTA
This document summarizes research on clustering categorical data for internet security applications. It discusses using clustering techniques for malware categorization, phishing website detection, and detecting secure emails. Feature extraction and categorization are generally used to automatically group file samples or websites. The document also reviews several related works applying clustering and other techniques for malware analysis, phishing detection, and analyzing privacy-breaching malware behavior.
Today's security is that the main downside and every one the work is finished over the net mistreatment knowledge. whereas the information is out there, there square measure many varieties of users who act with knowledge and a few of them for his or her would like it all for his or her gaining data. There square measure numerous techniques used for cover of information however the hacker or cracker is a lot of intelligent to hack the security, there square measure 2 classes of hackers theyre completely different from one another on the idea of their arrange. The one who has smart plans square measure referred to as moral hackers as a result of the ethics to use their talent and techniques of hacking to supply security to the organization. this idea describes concerning the hacking, styles of hackers, rules of moral hacking and also the blessings of the moral hacking. Mukesh. M | Dr. S. Vengateshkumar "Ethical Hacking" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29351.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/29351/ethical-hacking/mukesh-m
This document presents a proposed machine learning-based Android malware detection system. It discusses how Android devices are increasingly being targeted by malware due to the open nature of the Android app marketplace. The proposed system would use machine learning classifiers to analyze permission-based features and events from Android apps to classify them as goodware or malware. It would monitor apps and detect malware to enhance security and privacy for smartphone users. The system design uses k-means clustering and naive Bayes classification on XML and DEX file features to detect malware in two layers if needed.
This document discusses honeypots, which are fake computer systems designed to attract hackers. Honeypots monitor the activity of hackers and collect data on their tactics. They are classified based on their level of interaction (low or high) and implementation environment (research or production). Honeypots provide advantages like detecting new hacking tools and minimizing resources needed. They also have disadvantages like limited visibility and risk of being hijacked. The document discusses practical applications of honeypots for preventing attacks, detecting intrusions, and conducting cyber forensics investigations.
Ransomware has become a lucrative criminal enterprise, with cyber criminals extorting over $209 million from organizations in just the first three months of 2016 alone. Ransomware works by encrypting files on infected machines and demanding ransom payments in exchange for the decryption key. While early ransomware dated back to 2005, the threat grew significantly in 2015 with over 400,000 infections and $325 million stolen. Ransomware variants now aim to disrupt device usage until payment is made. Organizations can help mitigate the risk of ransomware through practices like regular backups, keeping software updated, limiting user privileges, and restricting unknown applications.
Honey pots can be implemented in cloud computing to improve security. There are several components, including a cloud controller, cluster controller, honey controller, and log storage system. Low interaction honey pots like Honeyd emulate services to detect attacks, while high interaction honey pots like Honeynets allow more flexibility for attackers but carefully control outbound traffic. Honey pots can be offered as a service for cloud customers, providing logs and statistics to help secure resources against future attacks.
Viruses & Malware: Effects On Enterprise NetworksDiane M. Metcalf
The document discusses viruses and malware, focusing on three key areas: detection, disinfection, and related costs for enterprise networks. It describes popular methods of malware infection like exploits, social engineering, rogue infections, peer-to-peer file sharing, emails, and USB devices. It also discusses different types of malware like metamorphic and polymorphic malware, and how they avoid detection through techniques like obfuscation. Current detection methods include signature-based analysis, file emulation, and file analysis, as well as emerging approaches like traffic analysis and vulnerability scanning. Disinfection includes removing malware through specific tools, real-time scanners, and cloud-based technologies. The document outlines how to quantify direct and indirect costs of
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516Yasser Mohammed
This document discusses how three cyber threats - targeted attacks, system exploits, and data theft - are transforming incident response. It provides three case studies:
1) Operation Aurora targeted Google and other companies through a multi-stage attack using custom malware. Cyberforensics tools could have helped identify compromised systems and collect evidence.
2) The Zeus botnet exploits systems by infecting them and forwarding login credentials. Regular scans using cyberforensics tools can establish a baseline and detect any anomalies to address risks.
3) Data loss or theft of regulated/sensitive data from laptops or compromised websites can result in lost revenue and reputation damage. Cyberforensics tools can help find and wipe such data from unauthorized
This document discusses cyber security and tasks related to preventing cyber attacks. It covers different types of frauds and scams like malware, phishing attacks, and ransomware. It provides methods to prevent these attacks, such as avoiding unknown emails, using strong passwords, and keeping anti-virus software updated. Network monitoring tools like Wireshark are described that can detect malware by analyzing network traffic and ports. Laws related to cyber crimes in New Zealand are also summarized. Common denial of service attacks and methods to design protective systems are outlined, including using firewalls, intrusion detection, and anti-malware programs.
This document presents a proposed system for detecting phishing websites using a Chrome extension. The system compares URLs to entries in two databases - the Phishtank database of known phishing sites, and a local IndexedDB of frequently visited sites. If a match is found in either database, the Chrome extension will flag the site as potentially malicious by changing color. The system was tested on 53 URLs, achieving an accuracy of 92.45% at detecting phishing sites. The proposed system aims to alert users to phishing sites and protect them from disclosing sensitive information to attackers.
This document discusses honeypots and the honeyd software. Honeypots are decoy servers that are used to detect intruders by appearing as normal servers but containing fake data. Honeyd is a honeypot daemon that can simulate a large network using a single host by creating virtual hosts with different personalities. It is used for distraction, detecting suspicious traffic, and learning about attack techniques. The document describes how to configure honeyd by setting virtual host properties and firewall rules to forward traffic to it.
Intelligent Phishing Website Detection and Prevention System by Using Link Gu...IOSR Journals
The document discusses an intelligent phishing website detection and prevention system that uses a Link Guard algorithm. It analyzes the characteristics of hyperlinks used in phishing attacks, such as the visual link and actual link not matching, use of IP addresses instead of domain names, and use of encoded or similar-looking domain names. The document then proposes the Link Guard algorithm, which is implemented in Windows XP. Experiments show Link Guard can effectively detect 195 out of 203 known phishing attacks with minimal false negatives, using only the generic characteristics of phishing hyperlinks rather than signatures of specific attacks.
IRJET- Identification of Clone Attacks in Social Networking SitesIRJET Journal
This document discusses identifying clone attacks in social networking sites. It proposes a two-level approach using fuzzy-sim algorithm for profile matching and three algorithms (Predictive FP Growth, Eclat, and Apriori) for user activity matching. An experiment compares the execution times of the three algorithms, finding that Predictive FP Growth has the fastest time of 181 milliseconds, making it best for user activity matching.
This document provides an overview of offensive open-source intelligence (OSINT) techniques. It defines OSINT and discusses the differences between offensive and defensive OSINT approaches. Offensive OSINT focuses on gathering as much public information as possible to facilitate an attack against a target. The document outlines the OSINT process and details specific techniques for harvesting data from public sources, including scraping websites, using APIs, searching social media, analyzing images and metadata, and researching infrastructure components like IP addresses, domains, and software versions. The goal of offensive OSINT is to discover valuable information like employee emails, usernames, relationships, locations and technical vulnerabilities to enable attacks like phishing, social engineering, and infiltration.
This document discusses leveraging advanced persistent threat (APT) indicator feeds with enterprise security information and event management (SIEM/SEM) systems to improve cybersecurity incident detection accuracy. It presents a framework for developing use cases that integrate threat intelligence data to identify potential gaps in antivirus detection, improperly categorized domains in web proxies, and data exfiltration from malware-infected hosts. The framework is intended to increase incident detection accuracy, improve investigation quality, and create a knowledge base for threat intelligence.
This document provides definitions and explanations of honeypots and honeynets. It begins by defining a honeypot as a resource that pretends to be a real target in order to gather information about attacks without putting real systems at risk. There are different types of honeypots including research/production honeypots and low/high interaction honeypots. Honeynets are networks of multiple honeypot systems that allow for containment of attackers and capture of all activity. Virtual honeynets deploy entire honeynet architectures virtually on single systems. The document outlines advantages like flexibility and minimal resources, and disadvantages like narrow field of view and risk of fingerprinting.
Threat hunting involves proactively searching networks to detect threats like advanced persistent threats that evade existing security systems. It is done through a hunting loop of forming hypotheses based on analytics, intelligence, or situational awareness, investigating through tools and data, uncovering patterns and indicators, and informing analytics. Various methods can be used for hunting like DNS fuzzing to find malicious domains, analyzing passive DNS data, web server logs, emails, and Windows logs. Open source tools used include Maeltego CE, YARA, and AIEngine, while commercial tools are Sqrrl, Exabeam, Infocyte HUNT, Mantix4, and AI Hunter.
The document discusses ethical hacking and summarizes:
1) Ethical hackers evaluate the security of systems by using the same techniques as criminal hackers but without causing damage or theft, in order to identify vulnerabilities and help clients strengthen their security.
2) Successful ethical hackers have strong technical skills as well as trustworthiness, patience, and a drive to continuously improve security. They conduct thorough evaluations that simulate real attacks.
3) The goal of an ethical hack is to answer what information an intruder could access, what they could do with it, and whether the target would notice intrusion attempts, in order to identify security weaknesses before criminals can exploit them.
A survey on detection of website phishing using mcac techniquebhas_ani
This document discusses a technique called Multi-label Classifier based Associative Classification (MCAC) for detecting phishing websites. MCAC is a data mining approach that uses machine learning algorithms to generate rules for classifying websites as phishing or legitimate. It works by extracting features from websites and training a classifier on these features to accurately identify phishing websites. The proposed system uses MCAC to extract 16 features from websites and generate rules to classify websites, with the goal of detecting phishing attacks and warning users. MCAC is shown to identify phishing websites with high accuracy.
The Honeynet Project is a non-profit organization that aims to improve internet security by learning about computer attacks. It deploys honeypots - computers designed to be hacked - to capture data on threats. The organization shares its research findings openly. It also operates a Honeynet Research Alliance of groups around the world collaborating on honeypot technologies and research.
This ppt contains all the basics of honeypots like their types, implementation technologies, position in the network etc.
In the end, it contains a screenshot of a live honeypot processing.
APT 28 :Cyber Espionage and the Russian Government?anupriti
Russia may be behind a long-standing, careful campaign designed to steal sensitive data relating to governments, militaries and security firms worldwide.This presentation based on a report made public by FireEye brings an over view of their opinion.....uploaded here just for general info to understand how its all happening!!!!
The document discusses the future of libraries and the University of Technology Sydney (UTS) Library's plans for transitioning to Library 3.0. UTS Library will relocate in two stages, first installing an underground Library Retrieval System in 2014 and then moving to a new Learning Commons building by 2016. About 75-80% of the collection will be housed in the retrieval system, freeing up space for customized physical spaces and personalized web services to help users search for and discover resources.
This document discusses honeypots, which are fake computer systems designed to attract hackers. Honeypots monitor the activity of hackers and collect data on their tactics. They are classified based on their level of interaction (low or high) and implementation environment (research or production). Honeypots provide advantages like detecting new hacking tools and minimizing resources needed. They also have disadvantages like limited visibility and risk of being hijacked. The document discusses practical applications of honeypots for preventing attacks, detecting intrusions, and conducting cyber forensics investigations.
Ransomware has become a lucrative criminal enterprise, with cyber criminals extorting over $209 million from organizations in just the first three months of 2016 alone. Ransomware works by encrypting files on infected machines and demanding ransom payments in exchange for the decryption key. While early ransomware dated back to 2005, the threat grew significantly in 2015 with over 400,000 infections and $325 million stolen. Ransomware variants now aim to disrupt device usage until payment is made. Organizations can help mitigate the risk of ransomware through practices like regular backups, keeping software updated, limiting user privileges, and restricting unknown applications.
Honey pots can be implemented in cloud computing to improve security. There are several components, including a cloud controller, cluster controller, honey controller, and log storage system. Low interaction honey pots like Honeyd emulate services to detect attacks, while high interaction honey pots like Honeynets allow more flexibility for attackers but carefully control outbound traffic. Honey pots can be offered as a service for cloud customers, providing logs and statistics to help secure resources against future attacks.
Viruses & Malware: Effects On Enterprise NetworksDiane M. Metcalf
The document discusses viruses and malware, focusing on three key areas: detection, disinfection, and related costs for enterprise networks. It describes popular methods of malware infection like exploits, social engineering, rogue infections, peer-to-peer file sharing, emails, and USB devices. It also discusses different types of malware like metamorphic and polymorphic malware, and how they avoid detection through techniques like obfuscation. Current detection methods include signature-based analysis, file emulation, and file analysis, as well as emerging approaches like traffic analysis and vulnerability scanning. Disinfection includes removing malware through specific tools, real-time scanners, and cloud-based technologies. The document outlines how to quantify direct and indirect costs of
EXTERNAL - Whitepaper - How 3 Cyber ThreatsTransform Incident Response 081516Yasser Mohammed
This document discusses how three cyber threats - targeted attacks, system exploits, and data theft - are transforming incident response. It provides three case studies:
1) Operation Aurora targeted Google and other companies through a multi-stage attack using custom malware. Cyberforensics tools could have helped identify compromised systems and collect evidence.
2) The Zeus botnet exploits systems by infecting them and forwarding login credentials. Regular scans using cyberforensics tools can establish a baseline and detect any anomalies to address risks.
3) Data loss or theft of regulated/sensitive data from laptops or compromised websites can result in lost revenue and reputation damage. Cyberforensics tools can help find and wipe such data from unauthorized
This document discusses cyber security and tasks related to preventing cyber attacks. It covers different types of frauds and scams like malware, phishing attacks, and ransomware. It provides methods to prevent these attacks, such as avoiding unknown emails, using strong passwords, and keeping anti-virus software updated. Network monitoring tools like Wireshark are described that can detect malware by analyzing network traffic and ports. Laws related to cyber crimes in New Zealand are also summarized. Common denial of service attacks and methods to design protective systems are outlined, including using firewalls, intrusion detection, and anti-malware programs.
This document presents a proposed system for detecting phishing websites using a Chrome extension. The system compares URLs to entries in two databases - the Phishtank database of known phishing sites, and a local IndexedDB of frequently visited sites. If a match is found in either database, the Chrome extension will flag the site as potentially malicious by changing color. The system was tested on 53 URLs, achieving an accuracy of 92.45% at detecting phishing sites. The proposed system aims to alert users to phishing sites and protect them from disclosing sensitive information to attackers.
This document discusses honeypots and the honeyd software. Honeypots are decoy servers that are used to detect intruders by appearing as normal servers but containing fake data. Honeyd is a honeypot daemon that can simulate a large network using a single host by creating virtual hosts with different personalities. It is used for distraction, detecting suspicious traffic, and learning about attack techniques. The document describes how to configure honeyd by setting virtual host properties and firewall rules to forward traffic to it.
Intelligent Phishing Website Detection and Prevention System by Using Link Gu...IOSR Journals
The document discusses an intelligent phishing website detection and prevention system that uses a Link Guard algorithm. It analyzes the characteristics of hyperlinks used in phishing attacks, such as the visual link and actual link not matching, use of IP addresses instead of domain names, and use of encoded or similar-looking domain names. The document then proposes the Link Guard algorithm, which is implemented in Windows XP. Experiments show Link Guard can effectively detect 195 out of 203 known phishing attacks with minimal false negatives, using only the generic characteristics of phishing hyperlinks rather than signatures of specific attacks.
IRJET- Identification of Clone Attacks in Social Networking SitesIRJET Journal
This document discusses identifying clone attacks in social networking sites. It proposes a two-level approach using fuzzy-sim algorithm for profile matching and three algorithms (Predictive FP Growth, Eclat, and Apriori) for user activity matching. An experiment compares the execution times of the three algorithms, finding that Predictive FP Growth has the fastest time of 181 milliseconds, making it best for user activity matching.
This document provides an overview of offensive open-source intelligence (OSINT) techniques. It defines OSINT and discusses the differences between offensive and defensive OSINT approaches. Offensive OSINT focuses on gathering as much public information as possible to facilitate an attack against a target. The document outlines the OSINT process and details specific techniques for harvesting data from public sources, including scraping websites, using APIs, searching social media, analyzing images and metadata, and researching infrastructure components like IP addresses, domains, and software versions. The goal of offensive OSINT is to discover valuable information like employee emails, usernames, relationships, locations and technical vulnerabilities to enable attacks like phishing, social engineering, and infiltration.
This document discusses leveraging advanced persistent threat (APT) indicator feeds with enterprise security information and event management (SIEM/SEM) systems to improve cybersecurity incident detection accuracy. It presents a framework for developing use cases that integrate threat intelligence data to identify potential gaps in antivirus detection, improperly categorized domains in web proxies, and data exfiltration from malware-infected hosts. The framework is intended to increase incident detection accuracy, improve investigation quality, and create a knowledge base for threat intelligence.
This document provides definitions and explanations of honeypots and honeynets. It begins by defining a honeypot as a resource that pretends to be a real target in order to gather information about attacks without putting real systems at risk. There are different types of honeypots including research/production honeypots and low/high interaction honeypots. Honeynets are networks of multiple honeypot systems that allow for containment of attackers and capture of all activity. Virtual honeynets deploy entire honeynet architectures virtually on single systems. The document outlines advantages like flexibility and minimal resources, and disadvantages like narrow field of view and risk of fingerprinting.
Threat hunting involves proactively searching networks to detect threats like advanced persistent threats that evade existing security systems. It is done through a hunting loop of forming hypotheses based on analytics, intelligence, or situational awareness, investigating through tools and data, uncovering patterns and indicators, and informing analytics. Various methods can be used for hunting like DNS fuzzing to find malicious domains, analyzing passive DNS data, web server logs, emails, and Windows logs. Open source tools used include Maeltego CE, YARA, and AIEngine, while commercial tools are Sqrrl, Exabeam, Infocyte HUNT, Mantix4, and AI Hunter.
The document discusses ethical hacking and summarizes:
1) Ethical hackers evaluate the security of systems by using the same techniques as criminal hackers but without causing damage or theft, in order to identify vulnerabilities and help clients strengthen their security.
2) Successful ethical hackers have strong technical skills as well as trustworthiness, patience, and a drive to continuously improve security. They conduct thorough evaluations that simulate real attacks.
3) The goal of an ethical hack is to answer what information an intruder could access, what they could do with it, and whether the target would notice intrusion attempts, in order to identify security weaknesses before criminals can exploit them.
A survey on detection of website phishing using mcac techniquebhas_ani
This document discusses a technique called Multi-label Classifier based Associative Classification (MCAC) for detecting phishing websites. MCAC is a data mining approach that uses machine learning algorithms to generate rules for classifying websites as phishing or legitimate. It works by extracting features from websites and training a classifier on these features to accurately identify phishing websites. The proposed system uses MCAC to extract 16 features from websites and generate rules to classify websites, with the goal of detecting phishing attacks and warning users. MCAC is shown to identify phishing websites with high accuracy.
The Honeynet Project is a non-profit organization that aims to improve internet security by learning about computer attacks. It deploys honeypots - computers designed to be hacked - to capture data on threats. The organization shares its research findings openly. It also operates a Honeynet Research Alliance of groups around the world collaborating on honeypot technologies and research.
This ppt contains all the basics of honeypots like their types, implementation technologies, position in the network etc.
In the end, it contains a screenshot of a live honeypot processing.
APT 28 :Cyber Espionage and the Russian Government?anupriti
Russia may be behind a long-standing, careful campaign designed to steal sensitive data relating to governments, militaries and security firms worldwide.This presentation based on a report made public by FireEye brings an over view of their opinion.....uploaded here just for general info to understand how its all happening!!!!
The document discusses the future of libraries and the University of Technology Sydney (UTS) Library's plans for transitioning to Library 3.0. UTS Library will relocate in two stages, first installing an underground Library Retrieval System in 2014 and then moving to a new Learning Commons building by 2016. About 75-80% of the collection will be housed in the retrieval system, freeing up space for customized physical spaces and personalized web services to help users search for and discover resources.
The document discusses the ongoing European debt crisis and risks to the US economy. It analyzes the positions of various players in the European crisis including Germany, the ECB, and affected countries. There are disagreements around who should bear the costs of bailouts. The document also notes weakness in US data but argues against an imminent recession, though growth is expected to remain weak. More quantitative easing by the Fed is anticipated but benefits are uncertain. Low valuations reflect high recession probabilities priced into markets.
Richard Edelman discusses how PR is changing in a world with new media. The traditional top-down model of PR is giving way to a hybrid model where companies engage in both top-down messaging and peer-to-peer conversations. Trust in institutions has declined so companies must work to build trust through transparency, dialogue and participation with consumers online. PR professionals now facilitate conversations rather than just pitch stories to traditional media.
This document is a collection of photographs from the Italian American Cultural Center of Pennsylvania documenting the experiences of Italian immigrants in Berks County from the 1920s-1950s. The photos show immigrant workers on railroads in Reading in the 1920s, families from Italy in the late 1920s, certificates of naturalization, weddings at Holy Rosary Church, families gathered at Holy Rosary School, and scenes from the construction of the new Holy Rosary Church building in the 1950s. The collection aims to pay tribute to the contributions of Italian immigrants to the local community.
UTS Library future service model (with notes)Mal Booth
The UTS Library is exploring new service models to better meet the needs of students in the future. This includes relocating most of the physical collection to an underground retrieval system to free up space. New services will focus on improved search and discovery, cultural and learning hubs, customizable spaces, and 24/7 operations. Engagement initiatives like Fun Day have been successful in attracting hundreds of students through interactive activities and competitions.
Lab-4 Reconnaissance and Information Gathering A hacker.docxLaticiaGrissomzz
Lab-4: Reconnaissance and Information Gathering
A hacker uses many tools and methods to gather information about the target. There are two broad categories of information gathering methods: passive and active. These methods are detailed in the table below. In this lab, you will perform passive information gathering (gray-shaded column). In Lab 5, you will be performing active information gathering. Please review the table before starting this lab.
Information Gathering
Passive (Reconnaissance and Information Gathering) – This Week
Active (Scanning and Enumeration) – Next Week
Is the hacker contact with the target directly?
No direct contact with the target
Direct contact with the target
Are the activities logged?
No audit records on the target
Audit record might be created
What kind of tools has been used?
Web archives, Whois service, DNS servers, Search Engines
Port scanners, network scanners, vulnerability scanners (Nessus, Nmap)
What information can a hacker collect?
IP addresses, network range, telephone numbers, E-mail addresses, active machines, operating system version, network topology
Live hosts on a network, network topology, OS version, open ports on hosts, services running on hosts, running applications and their versions, patching level, vulnerabilities.
In passive information gathering, the hacker does not directly contact the target; therefore, no audit logs have been created. Both non-technical (such as employee names, birth dates, e-mail addresses) and technical information (IP addresses, domain names) can be gathered. This information can be used in many ways in the subsequent steps of the attack. For example, the phone numbers or e-mail addresses you discovered can be used in social engineering attacks. DNS records or subdomain names can be used to leverage specific attacks against hosts or URLs.
More notes on Reconnaissance and Information Gathering :
1) In this phase, an attacker may collect a lot of information without being noticed.
2) In some cases, an attacker may even discover vulnerabilities.
3) The information collected in this phase can be quite valuable when evaluated together with the information collected in the scanning and enumeration phase. For example, you might find the phone number and name of an employee in this phase, and you may find the computer IP address in the active scanning phase. You can use these two pieces of information together to leverage a social engineering attack. An attacker will increase the chance of gaining trust when s/he calls the victim's name and talk some specific about the victim's computer.
4) Companies should also perform reconnaissance and information gathering against themselves so that they can discover -before hackers- what kind of information the company and company employees disclose.
In this lab, you will practice 6 passive methods of Reconnaissance and Information Gathering. You have to use Kali VM in Sections 3, 5, and 6 of the lab. You may use Kali.
This document proposes using network-based signatures to detect spyware. It analyzes common spywares, how they operate, and their network activity. Network signatures are proposed that could detect spywares by analyzing outgoing network packets and correlating them with browser activity, allowing detection of keyloggers and other spying software beyond just adware.
This document discusses the design and implementation of a hybrid client honeypot that incorporates features of both low and high interaction honeypots. The hybrid honeypot aims to detect client-side malware attacks by actively visiting websites while also monitoring the system for any malware downloaded without user interaction, like zero-day attacks. It analyzes detected malware to classify known and unknown malware varieties. The hybrid approach combines the fast processing of low interaction honeypots with the ability of high interaction honeypots to detect zero-day attacks.
This document discusses the design and implementation of a hybrid client honeypot that incorporates features of both low and high interaction honeypots. It aims to detect client-side attacks by actively visiting websites while also monitoring the system for malware. The hybrid approach aims to overcome limitations of existing client honeypots by detecting zero-day attacks while remaining efficient. It discusses background on honeypots, client honeypots, and detection approaches. The system framework incorporates both emulation and real execution to balance detection abilities and resource usage.
This report from Imperva’s Hacker Intelligence Initiative (HII), describes a Search Engine Poisoning (SEP) campaign from start to finish. SEP abuses the ranking algorithms of search engines to promote an attacker-controlled Web site that contains malware. Imperva’s Application Defense Center (ADC) has witnessed these types of automated attack campaigns, which cause search engines to return high-ranking Web pages infected with malicious code that references an attacker-controlled Web site.
A Mitigation Technique For Internet Security Threat of Toolkits AttackCSCJournals
The development of attack toolkits conforms that cybercrime is driven primarily by financial motivations as noted from the significant profits made by both the developers and buyers. In this paper, an enhanced hybrid attack toolkit mitigation model was designed to tackle the economy of the attack toolkits using different techniques to discredit it. The mitigation looked into Zeus, a common and the most frequently used attack toolkit to discover the hidden information used by the attackers to launch attacks. This information helped in creating honey toolkits, honeybot and honeytokens. Honeybots are used to submit honeytoken to botmasters, who sells to the internet black market. Both the botmasters, his mules and buyers attempts to steal huge amount of money using the stolen credentials which includes both real and honeytokens and will be detected by an attack detector which sends an alert on any transaction involving the honeytokens. A reconfirmation process which is secured using enhanced RC6 cryptosystem is enacted. The reconfirmation message in plain text is securely encrypted into cipher text and transmitted from the bank to the legitimate account owner and vise visa. The result of the crypto analysis carried out on the encrypted text using RC6 encryption algorithm showed that the cipher text is not transparent.
Phishing is the fraudulent acquisition of personal information like username, password, credit card information, etc. by tricking an individual into believing that the attacker is a trustworthy entity. It is affecting all the major sector of industry day by day with lots of misuse of user’s credentials. So in today
online environment we need to protect the data from phishing and safeguard our information, which can be done through anti-phishing tools. Currently there are many freely available anti-phishing browser extensions tools that warns user when they are browsing a suspected phishing site. In this paper we did a literature survey of some of the commonly and popularly used anti-phishing browser extensions by reviewing the existing anti-phishing techniques along with their merits and demerits.
Invesitigation of Malware and Forensic Tools on Internet IJECEIAES
Malware is an application that is harmful to your forensic information. Basically, malware analyses is the process of analysing the behaviours of malicious code and then create signatures to detect and defend against it.Malware, such as Trojan horse, Worms and Spyware severely threatens the forensic security. This research observed that although malware and its variants may vary a lot from content signatures, they share some behaviour features at a higher level which are more precise in revealing the real intent of malware. This paper investigates the various techniques of malware behaviour extraction and analysis. In addition, we discuss the implications of malware analysis tools for malware detection based on various techniques.
Hii assessing the_effectiveness_of_antivirus_solutionsAnatoliy Tkachev
The document summarizes a study that assessed the effectiveness of antivirus software in detecting newly created malware. Some key findings include:
- The initial detection rate of new viruses by antivirus software is less than 5%, and for some vendors it can take up to 4 weeks to detect a new virus.
- Free antivirus software from Avast and Emisoft had among the best detection capabilities, though they also had high false positive rates.
- Given the low effectiveness of antivirus software, the document suggests that enterprises and consumers should consider alternative security approaches and that compliance requirements around antivirus could be eased to allow budgets to be used more effectively.
Assessing the Effectiveness of Antivirus SolutionsImperva
How good is antivirus? How should enterprises invest in endpoint protection? Imperva collected and analyzed more than 80 previously non-cataloged viruses against more than 40 antivirus solutions. This report details our findings.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Survey of Keylogger in Cybersecurity Educationijtsrd
Keylogger applications try to retrieve exclusive statistics through covertly shooting consumer enter through keystroke tracking after which relaying these statistics to others, frequently for malicious purposes. Keyloggers hence pose a chief danger to commercial enterprise and private sports consisting of Internet transactions, online banking, email, or chat. To cope with such threats, now no longer most effective ought to customers be made aware of this form of malware, however software program practitioners and college students ought to additionally be knowledgeable withinside the layout, implementation, and tracking of powerful defenses towards distinctive keylogger attacks. This paper affords a case for incorporating keylogging in cybersecurity schooling. First, the paper affords a top level view of keylogger applications, discusses keylogger layout, implementation, and utilization, and affords powerful tactics to hit upon and save you keylogging attacks. Second, the paper outlines numerous keylogging tasks that may be integrated into an undergraduate computing software to train the subsequent technology of cybersecurity practitioners on this crucial topic. Raja Saha | Dr. Umarani Chellapandy "A Survey of Keylogger in Cybersecurity Education" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49471.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/49471/a-survey-of-keylogger-in-cybersecurity-education/raja-saha
IRJET - An Automated System for Detection of Social Engineering Phishing Atta...IRJET Journal
1) The document presents a machine learning approach to detect phishing URLs using logistic regression. It trains a logistic regression model on a dataset of 420,467 URLs that have been classified as either phishing or legitimate.
2) It preprocesses the URLs using tokenization before training the logistic regression model. The trained model is able to classify new URLs with 96% accuracy as either phishing or legitimate based on the URL features.
3) The proposed approach provides an automated way to detect phishing URLs in real-time and help prevent phishing attacks. Future work could involve developing a browser extension using this approach and increasing the dataset size for higher accuracy.
Imperva's ADC analyzed real-world traffic from sixty Web applications in order to identify attack patterns. The report demonstrates that, across a community of Web applications, early identification of attack sources and attack payloads can significantly improve the effectiveness of application security. Furthermore, it reduces the cost of decision making with respect to attack traffic across the community. Here's how, based on the traffic analyzed by the ADC: (1) multiple target SQL attackers generated nearly 6x their share of the population (2) multiple target comment spam attackers generated 4.3x their share of the population (3) multiple target RFI attackers generated 1.7x their share of the population (this amounted to 73% of total attacks).
Deep Learning based Threat / Intrusion detection systemAffine Analytics
The document describes a proposed intrusion/threat detection system with the following key components:
1. A feature engineering module to extract relevant features from organizational data like employee information and online activities.
2. A text processing and topic modeling module to analyze communications data and identify confidential information.
3. An internal threat detection system using deep learning to detect threats in real-time with a risk score and predefined response policies.
4. An external threat detection system using signatures and anomaly detection to enforce actions against external threats.
This document discusses using data mining techniques to detect spyware. It begins by defining spyware and artificial intelligence. It then discusses three AI approaches that have been applied to spyware detection: heuristic technology, neural network technology, and data mining techniques. It focuses on using breadth-first search (BFS) within a data mining approach. The document finds that data mining techniques achieve an overall accuracy of 90.5% in detecting spyware, performing better than traditional signature-based or heuristic-based methods.
Utilization Data Mining to Detect Spyware IOSR Journals
This document discusses using data mining techniques to detect spyware. It begins by defining spyware and artificial intelligence. It then discusses three AI approaches that have been applied to spyware detection: heuristic technology, neural network technology, and data mining techniques. It focuses on using breadth-first search (BFS) within a data mining approach. The document finds that data mining techniques perform better than traditional signature-based or heuristic-based detection methods, achieving an overall accuracy of 90.5% at detecting spyware using BFS algorithms.
HOST PROTECTION USING PROCESS WHITE-LISTING, DECEPTION AND REPUTATION SERVICESAM Publications,India
The Internet or World Wide Web has become prominent platform for business and commerce and is witnessing user growth with increased penetration of mobile Internet. Huge traffic is being generated, some of it being legitimate and the rest being malicious. Hence the implementation and maintenance of Information Security programs is been done .In the age of the Internet, protecting our information has become just as important as protecting our property. Malware authors have found and exploited new zero-day vulnerabilities resulting in damage to end-user system. Ransomware, a malware that has taken malware attacks to a new level by locking files of the affected user and demand Bitcoin payment to unlock those files. On the other hand the Volume and frequency of Distributed Denial of Service (DDoS) attacks have increased. Many unpatched machines without the knowledge of its owners have become a part of Botnets which carry out DDoS attacks. This paper focuses on strategies to be adopted to protect individual hosts from malware attacks and other types of intrusions using Deception, White-Listing and Reputation Services.
The document analyzes a spam campaign from April to June 2012 that distributed malware via the Blackhole Exploit Kit. It found 245 separate spam runs spoofing 17-40 organizations each month. The spam used social engineering to trick users into clicking links that led to compromised websites and exploit pages hosting the Blackhole Exploit Kit. These pages attempted to exploit vulnerabilities in browsers and software to download malware like ZeuS and Cridex. The campaign was highly effective due to its scale and use of redirection, compromised sites and thousands of URLs daily, making it difficult for traditional security methods to keep up.
Similar to Hii the convergence_of_google_and_bots_-_searching_for_security_vulnerabilities_using_automated_botnets (20)
This document provides an overview of Russia's theory and practice of information warfare. It discusses how Russia has developed its information warfare theory in opposition to Western concepts, drawing on Soviet-era psychological warfare techniques. It also examines the role of Russian geopolitical schools in popularizing and participating in information warfare. The document analyzes how Russia employed extensive propaganda in its recent operations related to Ukraine and Crimea to influence domestic and international public opinion.
This document provides a summary of China's "Three Warfares" concept, which includes psychological warfare, media warfare, and legal warfare. It describes each type of warfare and provides examples. Psychological warfare aims to undermine the enemy's will through operations targeting morale. Media warfare seeks to influence domestic and international public opinion in China's favor. Legal warfare uses international and domestic law to advance Chinese interests. Taiwan is a primary target of Chinese psychological operations efforts to influence its military and citizens. The document evaluates Three Warfares as an information warfare concept employed during peacetime and wartime to maximize the effects of military force.
This document is a satirical portrayal of a conversation between Barack Obama and an advisor about how to address the perceived threat of Anonymous. It suggests they consider using propaganda techniques like attaching negative labels to Anonymous, citing innocent victims, and creating a sense of bandwagon pressure to turn public opinion against Anonymous. The document also briefly outlines and critiques several classic propaganda techniques that could potentially be used, like poisoning devices, testimonials, and exploiting emotions like fear.
Cia culture-intelligence-berrett-cultural topographyMousselmal Tarik
This article introduces a new methodology called "Cultural Mapping" for intelligence analysis to better account for cultural factors. Cultural Mapping is designed to isolate and assess cultural variables influencing issues of intelligence interest and distinguish their degree of influence on decision-making and outcomes. The methodology aims to provide a more systematic and persuasive treatment of culture compared to how it is typically addressed peripherally in intelligence analysis. The authors developed Cultural Mapping to remedy perceived deficiencies in how the intelligence community incorporates cultural understanding and to improve analysis for policymakers.
1) The document provides 99 tips for maintaining and repairing corporate reputation.
2) Key tips include communicating openly during difficult times, taking responsibility for mistakes, monitoring employee sentiment, and being accessible as a leader.
3) Reputation recovery takes time, courage, and consistent small actions over an extended period.
All right reserved:
Daniele Marzoli1 and Luca Tommasi1 Contact Information
(1) Department of Biomedical Sciences, University “G. d’Annunzio”, Blocco A, Via dei Vestini 29, 66013 Chieti, Italy
Published on
http://blogsetie.blogspot.com
This document discusses fuzzing SMS implementations on smartphones to find vulnerabilities. It presents techniques for injecting SMS messages locally into iPhones, Android, and Windows Mobile devices without using the carrier network. The authors used the Sulley fuzzing framework to generate fuzzed SMS messages and monitor the phone software under stress. Their fuzzing found security issues that could crash or reboot devices or prevent further SMS reception.
Eiaa Marketers Internet Ad Barometer 2009 Pr PresentationMousselmal Tarik
Advertisers are increasing their online ad spending, with 70% reporting increases in 2009. On average, increases are predicted at 18% in 2009, 21% in 2010, and 15% in 2011. Most satisfied with internet advertising, 84% ranking it highly. Targeting by demographics like 25-44 year olds is increasing. Use of formats like search, display, and video are up. 16% of budgets on average are now spent at a pan-European rather than country level. Mobile and video seen as key drivers in coming years.
The document discusses a global survey on health attitudes. Some key findings include:
- Around the world, being healthy is highly valued while illness is seen negatively. Most people report being at least somewhat healthy.
- However, there are also widespread concerns about developing various illnesses like cancer or chronic conditions. People feel vulnerable to health problems outside their control.
- Recent world events have increased general anxiety and uncertainty. As wealth becomes less certain, health is becoming more important as something still within personal influence.
- Thinking about health is common. Those with lower incomes think about health more often, suggesting health is a priority when other aspects of life feel unpredictable.
Pharell dancing in a Mc Donald's restaurant in a Paris Airport... But after that what are the results on the Web? Who's taking advant-age of the buzz???
Analyse du buzz généré par la vidéo publiée par Pharell Williams lors de son passage dans un mc donalds de Paris (à l'aéroport de Roissy Charles de Gaulle)
The document outlines a design strategy for Pepsi called "BREATHTAKING" that draws inspiration from Pepsi's branding history and universal design principles to create a new identity. It explores how investigating a brand's roots can help propel it forward. The strategy aims to shift Pepsi from a conventional to innovative brand by developing an iconic shape based on geometric patterns found in past packaging. Circles placed in a specific proportional relationship are used to derive the new Pepsi identity and logo. Color palettes and dimensional effects are also discussed to enhance the multi-dimensional brand experience.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Hii the convergence_of_google_and_bots_-_searching_for_security_vulnerabilities_using_automated_botnets
1. August 2011
Hacker Intelligence Initiative, Monthly Trend Report #3
Hacker Intelligence Summary Report – The Convergence of Google and Bots:
Searching for Security Vulnerabilities using Automated Botnets
In this monthly report from Imperva’s Hacker Intelligence Initiative (HII), we describe
how popular search engines are used as an attack platform to retrieve sensitive Our findings show that during
an attack, hackers can generate
data, a.k.a. “Google Hacking”. This attack is further enhanced by deploying bots to more than 80,000 daily queries
automate the process and to evade anti-automation detection techniques commonly to probe the Web for vulnerable
Web applications.
deployed by the search engine providers. Although Google Hacking has been around
– in name – for some time, some new innovations by hackers require another, closer
look. Specifically, Google, and other search engines, put in place anti-automation measures to stop hackers from search abuse.
However, by using distributed bots, hackers take advantage of bot’s dispersed nature, giving search engines the impression that
individuals are performing a routine search. The reality? Hackers are conducting cyber reconnaissance on a massive scale.
Imperva’s Application Defense Center (ADC) has followed up on a particular botnet and has witnessed its usage against a
well-known search engine provider. By tracking this botnet, they found how attackers lay out the groundwork to simplify and
automate the next stages in an attack campaign against web applications. In this report, we describe the steps that hackers
take to leverage on the power of search engines to successfully carry out their attacks to massively collect attack targets. Our
findings show that during an attack, hackers can generate more than 80,000 daily queries to probe the Web for vulnerable
Web applications. We provide essential advice to organizations on how to prepare against exploits tailored against these
vulnerabilities. We also propose potential solutions that leading search engines such as Google, Bing and Yahoo can employ in
order to address the growing problem of hackers using their platform as an attacker tool.
An Overview of Google Hacking
On the Internet, search engines have emerged as powerful tools in an attacker’s arsenal, providing a way to gather
information about a target and find potential vulnerabilities in an anonymous and risk-free fashion. This activity is typically
called “Google Hacking”. Although the name emphasizes the search-engine giant, it pertains to all search engine providers.
Collecting information about an organization can set the stage for hackers to devise an attack tailored for a known
application. The specialized exploitation of known vulnerabilities may lead to contaminated web sites, data theft, data
modification, or even a compromise of company servers.
Search engines can be directed to return results that are focused on specific potential targets by using a specific set of
query operators. For example, the attacker may focus on all potential victims in a specified geographic location (i.e. per
country). In this case, the query includes a “location” search operator. In another scenario, an attacker may want to target
all vulnerabilities in a specific web site, and achieves this by issuing different queries containing the “site” search operator.
These particular search queries are commonly referred to as “Google Dorks”, or simply “Dorks”.
Automating the query and result parsing enables the attacker to issue a large number of queries, examine all the returned
results and get a filtered list of potentially exploitable sites in a very short time and with minimal effort.
In order to block automated search campaigns, today’s search engines deploy detection mechanisms which are based on
the IP address of the originating request.
2. Hacker Intelligence Initiative, Monthly Trend Report
What’s new about this attack campaign that we witnessed? Our investigation has shown that attackers are able to overcome
these detection techniques by distributing the queries across different machines. This is achieved by employing a network
of compromised machines, better known as botnet.
Hackers also gain the secondary benefit of hiding their identity behind these bots, since it is the compromised host which
actually performs the search queries. In effect, the attacker adds a layer of indirection between herself and the automated
search queries. This makes the task of tracking back the malicious activity to the individual attacker all the more difficult.
The Hacker’s 4 Steps for an Industrialized Attack:
1. Get a botnet. This is usually done by renting a botnet from a bot farmer who has a global network of compromised
computers under his control.
2. Obtain a tool for coordinated, distributed searching. This tool is deployed to the botnet agents and it usually
contains a database of dorks.
3. Launch a massive search campaign through the botnet. Our observations show that there is an automated
infrastructure to control the distribution of dorks and the examination of the results between botnet parts.
4. Craft a massive attack campaign based on search results. With the list of potentially vulnerable resources, the
attacker can create, or use a ready-made, script to craft targeted attack vectors that attempt to exploit vulnerabilities in
pages retrieved by the search campaign. Attacks include: infecting web applications, compromising corporate data or
stealing sensitive personal information.
Detailed Analysis
Mining Search Engines for Attack Targets
Search engine mining can be used by attackers in multiple ways. Exposing neglected sensitive files and folders, collecting
network intelligence from exposed logs and detecting unprotected network attached devices are some of the perks of
having access to this huge universal index. Our report focuses on one specific usage: massively collecting attack targets.
Specially crafted search queries can be constructed to detect web resources that are potentially vulnerable. There is a
wide variety of indicators, starting from distinguishable resource names through banners of specific products and up to
specific error messages. The special search terms, commonly referred to as “Dorks”1, combine search terms and operators
that usually correlate the type of resource with its contents. Dorks are commonly exchanged between hackers in forums.
Comprehensive lists of dorks are also being made available through various web sites (both public and underground).
Examples include the legendary Google Hacking Database at http://johnny.ihackstuff.com/ghdb/ and the up-to-date sites
http://www.1337day.com/webapps and http://www.exploit-db.com/google-dorks/. As the latter name suggests, the site
contains an exploit database demonstrating how dorks and exploits go hand in hand.
1
http://www.danscourses.com/Network-Security+/search-engine-hacking-471.html
Report #3, August 2011 2
3. Hacker Intelligence Initiative, Monthly Trend Report
Figure 1: Banner from the Google Hacking Database
Figure 2: Banners from the Exploit Database
Report #3, August 2011 3
4. Hacker Intelligence Initiative, Monthly Trend Report
Some resources classify dorks according to platform or usage as can be seen from the screenshot below:
Figure 3: Searching dorks by class
An attacker armed with a browser and a dork can start listing potential attack targets. By using search engine results an
attacker not only lists vulnerable servers but also gets a pretty accurate idea as to which resources within that server are
potentially vulnerable.
Report #3, August 2011 4
5. Hacker Intelligence Initiative, Monthly Trend Report
For example, the following query returns results of online shopping sites containing the Oscommerce application.
Figure 4: results returned from a dork search
Report #3, August 2011 5
6. Hacker Intelligence Initiative, Monthly Trend Report
The following screenshot returns results of a dork search for FTP configuration results
Figure 5: results returned from a dork search
Automating the Usage of Dorks
Tools to automate the use of dorks have been created over the years by attacker groups. Some of them are desktop tools
and some are accessible as an online service. Some automate just the collection of targets and others automate the
construction of exploit vector and the attack itself.
Figure 6: Desktop tool for automated Google Hacking
Report #3, August 2011 6
7. Hacker Intelligence Initiative, Monthly Trend Report
Figure 7: Online service for automated search and attack campaigns
In view of this threat, most search engines have implemented anti-automation measures that rely (mainly) on the
following attributes:
› Number of search queries from a single source (IP / session)
› Frequency of queries from a single source
› Massive retrieval of results for a single query
The anti-automation measures taken by search engine operators forced attackers to look for new alternatives for search
engine hacking automation. They found it in the form of botnet based search engine mining. By harnessing the power of
botnets, attackers launch distributed coordinated search campaigns that evade the standard anti-automation mechanisms.
The inherent distributed nature of the attack helps avoid the single source issue. The use of special search operators that
artificially split the search space (e.g. by country or by partial domain), overcomes the limitation enforced by search engines
over the number of results that can be retrieved per query. In addition, the attacker creates yet another layer of indirection
through the use of “search proxies”. This extra layer makes it even harder to identify the true source of the attack and the
whereabouts of the attacker.
In the following section we will show evidence of these techniques as seen in the wild.
A Typical Dork-Search Attack
We have observed a specific botnet attack on a popular search engine during May-June 2011. The attacker used dorks that
match vulnerable web applications and search operators that were tailored to the specific search engine. For each unique
search query, the botnet examined dozens and even hundreds of returned results using paging parameters in the query.
The volume of attack traffic was huge: nearly 550,000 queries (up to 81,000 daily queries, and 22,000 daily queries on
average) were requested during the observation period. It is clear that the attacker took advantage of the bandwidth
available to the dozens of controlled hosts in the botnet to seek and examine vulnerable applications.
Report #3, August 2011 7
8. Hacker Intelligence Initiative, Monthly Trend Report
Figure 8: dork queries per hour
Figure 9: dork queries per day
Search Engine Dorks
Most of the Dorks used in the observed attack were related to Content Management Systems and e-commerce applications.
Content Management Systems manage the work flow of users in a collaborative environment and enable a large number of
people to contribute to a site and to share stored data (for example, an eCommerce system or a forum for users of a game to
share playing tips). These systems are naturally more open and allow external users to contribute content and even upload
entire files. Thus, security vulnerabilities they contain can be easily exposed and exploited. E-commerce systems, on the
other hand, manage and store financial information about their customers, and a successful attack on such a site can be
immediately monetized.
Report #3, August 2011 8
9. Hacker Intelligence Initiative, Monthly Trend Report
Some examples of the observed dorks used in the attack are shown below. As can be seen, the search terms include various
free text words that identify vulnerable applications, as well as search operators that focus the query to specific sites,
domains or countries.
Example of vulnerabilities associated
Search Query Target application
with the application2
Oscommerce: online shop e-commerce SQL injection vulnerability in shopping_
“Powered By Oscommerce” ‘catalog’ solution cart.php (CVE-2006-4297)
“powered by oscommerce” shoping Oscommerce See above
allows remote attackers to execute arbitrary
“powered by e107” site:.ch e107 CMS; limited to servers in Switzerland PHP code (CVE-2010-2099)
“*.php?cPath=25” ranking Oscommerce See above
“powered by osCommerce” Oscommerce See above
Zen Cart Ecommerce; e-commerce web site Allows remote attackers to execute
“powered by zen cart” payment.php platform arbitrary SQL (CVE-2009-2254)
“powered by e107” global e107 CMS See above
e107 CMS - password reset page; limited to
“fpw.php” site:.ir See above
servers in Iran
Oscommerce German welcome page;
Herzlich Willkommen Gast! site:.de See above
limited to servers in Germany
e107 CMS; limited to domains with org
“powered by e107” site:.org See above
suffix)
BigCommerce e-commerce software
“by BigCommerce” joomla.ze See above
integrated with Joomla CMS
AppServe application development XSS vulnerability allows remote attackers to
“The Appserv Open Project” site:.th platform; limited to servers in Thailand. inject arbitrary web script (CVE-2008-2398)
e107 CMS; limited to domains with com
“Powered by e107 Forum System” site:.com See above
suffix
Joomla! es Software Libre distribuido bajo Joomla CMS - Spanish version See above
licencia GNU/GPL.
Directory Traversal vulnerability in
“com_rokdownloads” site:jp Joomla CMS; limited to servers in Japan RokDownloads component of Joomla (CVE-
2010-1056)
Table 1: Examples of observed dork queries
The additional operators (domain, language, etc.) as well as specification of the wanted page of results are used for
several purposes:
› Creating more focused result sets that allow construction of more accurate attack vectors
› Artificially splitting the search space in a way that distributes the workload of exhaustively examining the entire result
set between the bots in the net
Overall we have seen 4719 different dork variations being used in the attack (where “powered by e107” site:.ch and “powered
by e107” site:.fr are variation on the same basic dork). The 30 most-used dorks were related to osCommerse e-commerce
solution, and each of these variation appeared in 1,600-3,900 queries. The e107 application was the next popular attack
target based on the number of observed dorks.
2
For the applications that the attackers sought, these are examples of publicly disclosed vulnerabilities. However, these are not necessarily the
vulnerabilities that the attackers actually tried to exploit.
Report #3, August 2011 9
10. Hacker Intelligence Initiative, Monthly Trend Report
Botnet Hosts
Search engine providers identify malicious attacks based on a high volume or a high frequency of queries from the same
source. Yet we have witnessed how attackers bypass these detection mechanisms by employing a botnet.
During our observation period we have identified 40 different IP addresses of hosts that participate in the attacking botnet.
The hosts are not all active at the same time. The attack is distributed and coordinated. Thus, different hosts handle different
dorks and each host produces low rate search activity. We found that most hosts issue no more than one request every 2
minutes. However, four hosts together issue 2-4 requests per minute. This rate does not trigger the search engine’s anti-
automation policy as it normally cannot be considered abusive. In addition, the requests simulate a true browser activity
rather than a script by constantly changing the user-agent field. Consequently, the attack campaign can go on for a long
time, allowing the attacker to collect a substantial amount of target resources. An example of a coordinated distributed dork
search was for the dork “e107” using 99 different argument for the site search operator: 5 different hosts issued these queries
over the entire observation period.
Figure 10: hosts searching for the dork “e107” with a “site” operator
Figure 11: queries for the dork “e107” with a “site” operator
Report #3, August 2011 10
11. Hacker Intelligence Initiative, Monthly Trend Report
The botnet hosts are distributed all over the world. This is not surprising, since the attacker does not care about the location
or ownership of the abused hosts and just needs the ability to take control of these machines and add them to her network
of compromised computers. Thus, the identities of the botnet hosts give no direct indication to the identity of the hacker
that uses them for malicious attacks. However, it is interesting to note that the observed botnet has a disproportionate
number of servers in Iran, Hungary and Germany, and a low number of servers in the United States. Also, some of the
dork queries specifically limited results to servers in Iran or Germany. This combination may be a hint to the interests of
the attacker.
Figure 12: number of hosts issuing dork queries
Country # dork queries Percentage of dork queries
Islamic Republic of Iran 227554 41
Hungary 136445 25
Germany 80448 15
United States 19237 3.5
Chile 17365 3
Thailand 16717 3
Republic of Korea 11872 2
France 10906 2
Belgium 10661 2
Brazil 7559 1.5
Other 8892 2
Table 2: Countries of hosts issuing dork queries
Report #3, August 2011 11
12. Hacker Intelligence Initiative, Monthly Trend Report
Figure13: Countries of hosts issuing dork queries
Summary and Conclusions
We have observed a high-volume mining campaign of a botnet through a popular search engine. The campaign was
focused on finding resources that use specific content management frameworks that can be exploited.
While none of the components of the attack (use of botnets deployed on compromised servers, exploiting search
engine using dorks) are unique, it is interesting to observe the potential for automation and flexibility of the attack. Each
component may be replaced or reconfigured easily, while the attacker and tools remain hidden from targeted servers
and even the abused search engine. The impact of which would be for the attacker to create a map of hackable targets
on the Web.
This type of abuse should concern both the search engine providers as well as organizations. Search engines have
a responsibility to prevent attackers from taking advantage of their platform to carry out their attacks. At the same
time, search engines are in a unique position to identify botnets that abuse their services thus shedding light on the
attackers. Organizations should protect their applications from being publicly exposed through the search engines.
Recommendations to the Search Engines
Search engine providers are expected to perform a detailed analysis of network traffic which allows the flagging of
suspicious anomalies in the query traffic. Search engines typically look for low-level anomalies like high frequency or
high volume of requests from a host. As this report indicates, they should start looking for unusual suspicious queries
– such as those that are known to be part of public dorks-databases, or queries that look for known sensitive files (/etc
files or database data files).
Report #3, August 2011 12