BIG-IP 13.1.x reaches end of software development on December 31, 2022. F5 Advance WAF provides capabilities to detect and mitigate bot traffic accessing web applications. It uses anomaly detection to identify increases in request rates from sources like IP addresses, device IDs, URLs, or geolocations. It also has a dedicated anti-bot engine using bot signatures and anti-bot impersonation. When anomalies or bot detections occur, prevention options like client-side integrity checks, CAPTCHAs, or rate limiting can be applied. Reporting and dashboards provide visibility into bot activity and mitigation actions.
HTTP Brute Force Mitigation Playbook Bot Profile for Brute Force Mitigations ...Lior Rotkovitch
The document discusses configuration options for F5's Bot Defense profile in version 14.1 for mitigating brute force and credential stuffing attacks. It provides details on how to configure the bot profile settings such as the template mode, mitigation actions, browser verification, whitelisting, and reporting to classify and block bot traffic while allowing legitimate users. DNS and logging configurations are also required to be set up for proper bot detection and analytics.
Bots mitigations overview with advance waf anti bot engineLior Rotkovitch
With more and more bots traffic hitting web applications it has become a necessity to manage bots accessing web applications. To be able to manage bot access to your web application you must first be able to detect them and only then allow or deny them.
Those actions can be done by F5 advance WAF and this article will provide an overview of bot mitigations capabilities for versions 12.x , 13.x & 14.0
Advance WAF dos profile is a powerful bot management tool with various options to deal with bots. We classify them into two main types:
Anomaly based detection – anomaly engine to identify increase in RPS generated by bots
Proactive bot defense – a dedicated anti bot engine to identify bot activity
Let’s review each one of them in more details.
Did you know 30% of Ecommerce website visitors are unsavory competitors, hackers, and fraudsters?
Fact is, online retailers are particularly susceptible to the effects of advanced bot threats, including competitive tactics like price scraping, product matching, variation tracking and availability targeting. Even worse, security breaches such as transaction fraud and account takeovers endanger the overall security of your website, customer base, and brand.
When aggressive scrapers caused repeated site slowdowns, Brian Gress, Director of IT Systems & Governance at Hayneedle, said enough was enough.
Key takeaways include how to:
- Stop competitors from scraping your prices and monitoring your inventory
- Reduce chargeback fees due to transaction fraud, carding and account hijacking
- Optimize your conversion funnel and enjoy clean analytics and KPIs
- Protect your brand image, reputation and SEO rankings
AppSec EU 2016: Automated Mobile Application Security Assessment with MobSFAjin Abraham
Mobile Application market is growing like anything and so is the Mobile Security industry. With lots of frequent application releases and updates happening, conducting the complete security analysis of mobile applications becomes time consuming and cumbersome. In this talk I will introduce an extendable, and scalable web framework called Mobile Security Framework (https://github.com/ajinabraham/YSO-Mobile-Security-Framework) for Security analysis of Mobile Applications. Mobile Security Framework is an intelligent and automated open source mobile application (Android/iOS) pentesting and binary/code analysis framework capable of performing static and dynamic analysis. It supports Android and iOS binaries as well as zipped source code. During the presentation, I will demonstrates some of the issues identified by the tool in real world android applications. The latest Dynamic Analyzer module will be released at OWASP AppSec. Attendees Benefits * An Open Source framework for Automated Mobile Security Assessment. * One Click Report Generation and Security Assessment. * Framework can be deployed at your own environment so that you have complete control of the data. The data/report stays within the organisation and nothing is stored in the cloud. * Supports both Android and iOS Applications. * Semi Automatic Dynamic Analyzer for intelligent application logic based (whitebox) security assessment.
Ajin Abraham presented Mobile Security Framework (MobSF), an open source tool for mobile application security testing. MobSF includes static and dynamic analysis as well as a web API fuzzer. Static analysis scans the app code and binaries to detect vulnerabilities. Dynamic analysis monitors the app's network traffic and behavior through an agent. The web API fuzzer tests APIs for issues like IDOR, SSRF, and XXE. MobSF provides automated security testing to help mobile app developers and penetration testers.
How To Protect Your Website From Bot Attacks is a one-hour continuing education course. After successfully completing the course and final exam, you will be awarded a certificate of completion that you can use towards fulfilling your continuing education requirements.
This document discusses Wi-Fi security architectures, including captive portals, rogue access point detection and blocking, and wireless intrusion detection systems (WIDS). It provides details on how captive portals work using redirection, authorization, and connection processes. It describes methods for detecting rogue access points, including RF scanning, AP scanning, and using wired network inputs. It also outlines techniques for blocking rogue APs once detected, such as denial of service attacks or blocking the switch port. The document discusses the purpose and types of WIDS, including network-based and host-based systems, and passive versus reactive systems. It addresses best practices for deploying WIDS sensors and the technical expertise required to use WIDS effectively.
This document discusses how advanced persistent bots pose a threat to real estate portals by scraping listing data and spamming contact forms. Traditional homegrown solutions are ineffective against sophisticated bots. Lamudi, a global property portal, was experiencing performance issues and data scraping due to bot traffic 15x higher than human traffic. Lamudi implemented Distil's bot detection and mitigation solution, which uses techniques like device fingerprinting and browser validation to accurately identify and block bots without impacting users. This resulted in the elimination of data scraping, reduced form spam, improved performance, and saved engineering resources.
HTTP Brute Force Mitigation Playbook Bot Profile for Brute Force Mitigations ...Lior Rotkovitch
The document discusses configuration options for F5's Bot Defense profile in version 14.1 for mitigating brute force and credential stuffing attacks. It provides details on how to configure the bot profile settings such as the template mode, mitigation actions, browser verification, whitelisting, and reporting to classify and block bot traffic while allowing legitimate users. DNS and logging configurations are also required to be set up for proper bot detection and analytics.
Bots mitigations overview with advance waf anti bot engineLior Rotkovitch
With more and more bots traffic hitting web applications it has become a necessity to manage bots accessing web applications. To be able to manage bot access to your web application you must first be able to detect them and only then allow or deny them.
Those actions can be done by F5 advance WAF and this article will provide an overview of bot mitigations capabilities for versions 12.x , 13.x & 14.0
Advance WAF dos profile is a powerful bot management tool with various options to deal with bots. We classify them into two main types:
Anomaly based detection – anomaly engine to identify increase in RPS generated by bots
Proactive bot defense – a dedicated anti bot engine to identify bot activity
Let’s review each one of them in more details.
Did you know 30% of Ecommerce website visitors are unsavory competitors, hackers, and fraudsters?
Fact is, online retailers are particularly susceptible to the effects of advanced bot threats, including competitive tactics like price scraping, product matching, variation tracking and availability targeting. Even worse, security breaches such as transaction fraud and account takeovers endanger the overall security of your website, customer base, and brand.
When aggressive scrapers caused repeated site slowdowns, Brian Gress, Director of IT Systems & Governance at Hayneedle, said enough was enough.
Key takeaways include how to:
- Stop competitors from scraping your prices and monitoring your inventory
- Reduce chargeback fees due to transaction fraud, carding and account hijacking
- Optimize your conversion funnel and enjoy clean analytics and KPIs
- Protect your brand image, reputation and SEO rankings
AppSec EU 2016: Automated Mobile Application Security Assessment with MobSFAjin Abraham
Mobile Application market is growing like anything and so is the Mobile Security industry. With lots of frequent application releases and updates happening, conducting the complete security analysis of mobile applications becomes time consuming and cumbersome. In this talk I will introduce an extendable, and scalable web framework called Mobile Security Framework (https://github.com/ajinabraham/YSO-Mobile-Security-Framework) for Security analysis of Mobile Applications. Mobile Security Framework is an intelligent and automated open source mobile application (Android/iOS) pentesting and binary/code analysis framework capable of performing static and dynamic analysis. It supports Android and iOS binaries as well as zipped source code. During the presentation, I will demonstrates some of the issues identified by the tool in real world android applications. The latest Dynamic Analyzer module will be released at OWASP AppSec. Attendees Benefits * An Open Source framework for Automated Mobile Security Assessment. * One Click Report Generation and Security Assessment. * Framework can be deployed at your own environment so that you have complete control of the data. The data/report stays within the organisation and nothing is stored in the cloud. * Supports both Android and iOS Applications. * Semi Automatic Dynamic Analyzer for intelligent application logic based (whitebox) security assessment.
Ajin Abraham presented Mobile Security Framework (MobSF), an open source tool for mobile application security testing. MobSF includes static and dynamic analysis as well as a web API fuzzer. Static analysis scans the app code and binaries to detect vulnerabilities. Dynamic analysis monitors the app's network traffic and behavior through an agent. The web API fuzzer tests APIs for issues like IDOR, SSRF, and XXE. MobSF provides automated security testing to help mobile app developers and penetration testers.
How To Protect Your Website From Bot Attacks is a one-hour continuing education course. After successfully completing the course and final exam, you will be awarded a certificate of completion that you can use towards fulfilling your continuing education requirements.
This document discusses Wi-Fi security architectures, including captive portals, rogue access point detection and blocking, and wireless intrusion detection systems (WIDS). It provides details on how captive portals work using redirection, authorization, and connection processes. It describes methods for detecting rogue access points, including RF scanning, AP scanning, and using wired network inputs. It also outlines techniques for blocking rogue APs once detected, such as denial of service attacks or blocking the switch port. The document discusses the purpose and types of WIDS, including network-based and host-based systems, and passive versus reactive systems. It addresses best practices for deploying WIDS sensors and the technical expertise required to use WIDS effectively.
This document discusses how advanced persistent bots pose a threat to real estate portals by scraping listing data and spamming contact forms. Traditional homegrown solutions are ineffective against sophisticated bots. Lamudi, a global property portal, was experiencing performance issues and data scraping due to bot traffic 15x higher than human traffic. Lamudi implemented Distil's bot detection and mitigation solution, which uses techniques like device fingerprinting and browser validation to accurately identify and block bots without impacting users. This resulted in the elimination of data scraping, reduced form spam, improved performance, and saved engineering resources.
This document describes a web vulnerability scanner and reporting tool developed by researchers. The tool scans websites for various vulnerabilities like SQL injection, cross-site scripting, and file inclusion vulnerabilities. It performs scans both without login and with login credentials provided by the website owner. The without login scan checks if the site is reachable and identifies vulnerabilities, while the with login scan allows for deeper scanning. The tool uses machine learning, DOM, and aggregation algorithms. It produces a report with the number and types of vulnerabilities found, and URLs of affected pages. The researchers validated the tool and believe it can help developers identify and address security issues on their websites.
Automated web patrol with strider honey monkeys finding web sites that exploi...UltraUploader
The document describes the Strider HoneyMonkey Exploit Detection System, which uses virtual machines running automated "monkey programs" to patrol the web and detect websites that exploit browser vulnerabilities. Within the first month, the system identified 752 unique URLs operated by 287 websites that could successfully exploit unpatched Windows XP machines. The system tracks redirections between exploit sites to map their connections and identify major players.
Guarding Against Large-Scale Scrabble In Social NetworkEditor IJCATR
Generally, the botnet is one of the most dangerous threats in the network. It has number attackers in the network. The
attacker consists of DDOS attack, remote attack, etc., Bots perform perform repetitive tasks automatically or on a schedule over the
internet, tasks that would be too mundane or time-consuming for an actual person. But the botnets have stealthy behavior as they are
very difficult to identify. These botnets have to be identified and the internet have to be protected. Also the the activity of botnets must
be prevented to provide the users, a reliable service. The past of botnet detection has a transaction process which is not secure. A
efficient stastical data classifier is required to train the botent preventions system. To provide the above features clustering based
analysis is done. our approach can detect and profile various P2P applications rather than identifying a specific P2P application.
Anomaly based detection technique is used to obtain this goal.
Antivirus Techniques: Firewalls, Intrusion Detection System (IDS), Intrusion Prevention System (IPS).
Brief Introduction about Anti-Phishing Approach (Common Strategies Used For Secured Authentication): Authentication using passwords like One Time Password (OTP) generators, Two Factor Authentications, Secure Socket Layer (SSL), Secure Electronic Transaction (SET), Cryptography.
This document summarizes an approach to automatically detecting human and robot web traffic by analyzing HTTP request patterns. It describes using embedded JavaScript and CSS files to detect mouse/keyboard activity and standard browser behavior. Experiments on the CoDeeN content distribution network found this approach identified 95% of human users within 57 requests and 80% within 20 requests, with a maximum false positive rate of 2.4%. Since deploying this system, robot-related abuse complaints dropped by a factor of 10.
The Retail Strategy and Planning Series is designed to provide retail executives with the tactical tips, insights, metrics and trend data needed to guide 2017 strategies. Tune into Are Bot Operators Eating Your Lunch? and learn how to protect your brand image, reputation and SEO rankings from bad bots: rtou.ch/2c5cPmx.
The document discusses Cross Site Request Forgery (CSRF) attacks. It defines CSRF as an attack where unauthorized commands are transmitted from a user that a website trusts. The attack forces a logged-in user's browser to send requests, including session cookies, to a vulnerable website. This allows the attacker to generate requests the site thinks are from the user. The document outlines how CSRF works, example attacks, defenses for users and applications, and myths about CSRF. It recommends using unpredictable CSRF tokens or re-authentication to prevent CSRF vulnerabilities.
Verizon DMS' Bot Mitigation from Paul HobbsPaul Hobbs
The Verizon bot-mitigation solution helped StubHub identify and block bots performing scraping and fraud, which helped reduce transaction fraud and account takeovers. The solution uses device fingerprinting and behavioral analysis to detect and block 99.9% of malicious bots without impacting legitimate users. Verizon provides a dedicated security team and access to a database of known violators to help customers stay protected from emerging bot threats.
Vices & Devices - How IoT & Insecure APIs Became the New Cyber BattlefrontOry Segal
1. APIs have seen huge growth in usage, with over 25% of all internet traffic now consisting of API calls, largely driven by mobile apps and the growing IoT ecosystem.
2. Attackers have shifted focus to targeting APIs due to their simplicity and accessibility, exploiting common vulnerabilities like credential stuffing and application layer attacks against APIs developed with modern lightweight frameworks.
3. One campaign analyzed by Akamai showed attackers attempting 4 times as many stolen credentials through APIs compared to standard web logins, using over 4 times as many unique IP addresses per API-based campaign.
4. The rise of IoT devices has introduced new attack vectors, with credential abuse campaigns now exploiting vulnerable IoT devices like routers
Countering mobile malware in CSP’s network. Android honeypot as anti-fraud so...Denis Gorchakov
Honeypot is used for botnet analysis, traffic capturing and revealing C&C hostnames. It’s also used for detecting subscribers with infected devices and monitoring malware activities like funds withdrawal and remote control.
PHP is one of the most commonly used languages to develop web sites because of i
ts simplicity, easy to
learn and it can be easily embedded with any of the databases. A web developer with his basic knowledge
developing an application without practising secure guidelines, improper validation of user inputs leads to
various source code
v
ulnerabilities. Logical flaws while designing, implementing and hosting the web
application causes work flow deviation attacks.
In this paper, we are analyzing the complete behaviour of a
web application through static and dynamic analysis methodologies
State of the Art Analysis Approach for Identification of the Malignant URLsIOSRjournaljce
Malicious URLs have been universally used to ascend various cyber attacks including spamming, phishing and malware. Malware, short term for malicious software, is software which is developed to penetrate computers in a network without the user’s permission or notification. Existing methods typically detect malicious URLs of a single attack type. Hence such detection systems are failed to protect the users from various attacks. Malware spreading widely throughout the area of network as consequence of this it becomes predicament in distributed computer and network systems. Malicious links are the place of origin of all attacks which circulated all over the web. Hence malicious URLs should be detected for the prevention of users from these malware attacks. In this paper we described a novel approach which analyze all types of attacks by identifying malicious URLs and secure the web users from them. This technique prevents the users from malignant URLs before visiting them. Therefore efficiency of web security gets maintained. For such anatomization we developed an analyzer which identifies URLs and examine as malicious or benign. We also developed five processes which crawl for suspicious URLs. This approach will prevent the users from all types of attacks and increase efficiency of web crawling phase.
CEH v11 will teach you the latest commercial-grade hacking tools. Highlights of what sets CEH v11 apart from others are given in this SlideShare.
To learn more about CEH v11, click here: https://www.eccouncil.org/programs/certified-ethical-hacker-ceh/
Ensuring Property Portal Listing Data SecurityDistil Networks
Securing your property portal listing data is harder than ever. Why? Web scraping is cheap and easy. Bots simply steal whatever content they’ve been programmed to fetch – listing text, photos, and other data that should only be available to paid subscribers and legitimate consumers.
Review this presentation to learn how to avoid expensive litigation by protecting your content before the theft occurs. Review the latest research on how non-human traffic has evolved over the past few years and best practices to protect both copyrighted and non-copyrightable content.
Hear the results from research conducted with property portal executives on the current state of anti-scraping efforts.
This document proposes a web content analytics architecture to detect malicious JavaScript through real-time analysis of web traffic. It collects HTTP traffic using a proxy server and analyzes web content through static and dynamic analysis. Static analysis includes pattern matching, and dynamic analysis executes scripts to extract API call traces. Traces are clustered and signatures are generated by combining common tokens to detect similar malicious scripts while reducing false positives. The proposed approach analyzes JavaScript obfuscation and HTML5 usage to determine if further dynamic analysis is needed, and refines signatures through comparison to benign scripts. Evaluation showed the refined signatures improved detection rates while reducing false positives.
Distil Network Sponsor Presentation at the Property Portal Watch Conference -...Property Portal Watch
This document discusses ensuring security of property portal listing data from web scraping. It begins by defining web scraping as the automated copying of large amounts of data from websites. While some scraping is acceptable, malicious scraping can result in the theft of intellectual property like pricing, content, images and proprietary data from real estate portals. This damages brands through inaccurate data presentation and SEO impacts. The document notes that the cost of scraping has decreased while bot sophistication has increased, posing a growing problem for portals. However, most portals rely on outdated tools like IP blocking to address scraping that modern bots easily evade. Effective defenses require techniques like device fingerprinting and behavioral analysis. The session aims to help portals avoid expensive litigation by securing
Script based malware detection in online bankingJakub Kałużny
Online banking applications are particularly exposed to malware attacks. In order to prevent stealing from customer accounts, banks have invested in malware detection mechanisms. These programs are not installed on clients’ computers but rather implemented server-side or by including some JavaScript code on protected websites. We have tested such solutions which are using different detection methods. To name a few:
behavioral patterns,
web injects signatures,
user input analysis.
Our research points out clearly that even products sold as a „100% malware proof solutions” have serious implementation errors and it is only a matter of time when malware creators start targeting their guns against these vulnerabilities, effectively bypassing or abusing these countermeasures. Is it a road to failure or is there still time to improve these solutions? In this document we present security analysis of those solutions from attacker point of view and recommendations for improvement.
See also our presentation from Black Hat Asia and Confidence: „Bypassing malware detection mechanisms in online banking„
Nullcon Goa 2016 - Automated Mobile Application Security Testing with Mobile ...Ajin Abraham
Mobile Security Framework (MobSF) is an intelligent, all-in-one open source mobile application (Android/iOS) automated pen-testing framework capable of performing static and dynamic analysis. It can be used for effective and fast security analysis of Android and iOS Applications and supports both binaries (APK & IPA) and zipped source code. MobSF can also perform Web API Security testing with it's API Fuzzer that can do Information Gathering, analyze Security Headers, identify Mobile API specific vulnerabilities like XXE, SSRF, Path Traversal, IDOR, and other logical issues related to Session and API Rate Limiting.
Recognising Behavioural Patterns of Web API Bots Using Machine Learning Techn...Ravindra Guntur
Discovering bots that automate attacks and perform malicious actions is a key area of cyber security research. In this presentation we scope out the bot detection problem in the context of web API bots, and suggest how sequential neural network models can be used to solve the key problem of differentiating human behaviour from that of a malicious automaton.
Is Your API Being Abused – And Would You Even Notice If It Was?Nordic APIs
APIs are a wonderful thing and bring many benefits, but by their very nature they are also a window into how your business operates. If someone can exploit your system for gain, they will.
This presentation will give multiple real examples of API abuse in the wild, via methods such as data scraping, service misuse/cheating, unauthorized aggregation and fake account creation. How is it done, how are existing API controls bypassed, and what are the business implications?
The audience will learn that API abusers are inventive and they use smart tools. The audience will also learn who some of these API abusers are, and may be surprised by the result. (Spoiler: they can be your customers!)
Finally, some guidance will be given around what additional access controls can be put in place to ensure API based businesses continue to prosper.
Software management, the seasonal return of DDoS - This Week in Security.pdfLior Rotkovitch
This weekly security summary from F5 discusses several recent cybersecurity events:
- A proof of concept was published for a critical Fortinet vulnerability, leading to mass exploitation attempts.
- Automotive security threats are increasing as vehicles contain more software.
- Over 45,000 VMware ESXi servers reached end of support, leaving them vulnerable.
- A Minecraft server was hit with a record 2.5 terabit DDoS attack launched by the Mirai botnet.
- A pro-Russian group is paying people to participate in DDoS attacks against Western targets.
The 1B Data Leak, TrickBot Gang Shift and Cyber Espionage - F5 SIRT This Week...Lior Rotkovitch
This document provides a weekly summary of recent cybersecurity news from July 13th 2022. It discusses several major data breaches and cyber attacks that occurred, including a data leak of personal information on 1 billion Chinese citizens, ransomware attacks targeting the healthcare and NFT industries, and nation-state sponsored cyber espionage between China and Russia. The summary also provides technical details on newly discovered malware like Orbit targeting Linux devices and techniques used by the LockBit ransomware group.
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This document describes a web vulnerability scanner and reporting tool developed by researchers. The tool scans websites for various vulnerabilities like SQL injection, cross-site scripting, and file inclusion vulnerabilities. It performs scans both without login and with login credentials provided by the website owner. The without login scan checks if the site is reachable and identifies vulnerabilities, while the with login scan allows for deeper scanning. The tool uses machine learning, DOM, and aggregation algorithms. It produces a report with the number and types of vulnerabilities found, and URLs of affected pages. The researchers validated the tool and believe it can help developers identify and address security issues on their websites.
Automated web patrol with strider honey monkeys finding web sites that exploi...UltraUploader
The document describes the Strider HoneyMonkey Exploit Detection System, which uses virtual machines running automated "monkey programs" to patrol the web and detect websites that exploit browser vulnerabilities. Within the first month, the system identified 752 unique URLs operated by 287 websites that could successfully exploit unpatched Windows XP machines. The system tracks redirections between exploit sites to map their connections and identify major players.
Guarding Against Large-Scale Scrabble In Social NetworkEditor IJCATR
Generally, the botnet is one of the most dangerous threats in the network. It has number attackers in the network. The
attacker consists of DDOS attack, remote attack, etc., Bots perform perform repetitive tasks automatically or on a schedule over the
internet, tasks that would be too mundane or time-consuming for an actual person. But the botnets have stealthy behavior as they are
very difficult to identify. These botnets have to be identified and the internet have to be protected. Also the the activity of botnets must
be prevented to provide the users, a reliable service. The past of botnet detection has a transaction process which is not secure. A
efficient stastical data classifier is required to train the botent preventions system. To provide the above features clustering based
analysis is done. our approach can detect and profile various P2P applications rather than identifying a specific P2P application.
Anomaly based detection technique is used to obtain this goal.
Antivirus Techniques: Firewalls, Intrusion Detection System (IDS), Intrusion Prevention System (IPS).
Brief Introduction about Anti-Phishing Approach (Common Strategies Used For Secured Authentication): Authentication using passwords like One Time Password (OTP) generators, Two Factor Authentications, Secure Socket Layer (SSL), Secure Electronic Transaction (SET), Cryptography.
This document summarizes an approach to automatically detecting human and robot web traffic by analyzing HTTP request patterns. It describes using embedded JavaScript and CSS files to detect mouse/keyboard activity and standard browser behavior. Experiments on the CoDeeN content distribution network found this approach identified 95% of human users within 57 requests and 80% within 20 requests, with a maximum false positive rate of 2.4%. Since deploying this system, robot-related abuse complaints dropped by a factor of 10.
The Retail Strategy and Planning Series is designed to provide retail executives with the tactical tips, insights, metrics and trend data needed to guide 2017 strategies. Tune into Are Bot Operators Eating Your Lunch? and learn how to protect your brand image, reputation and SEO rankings from bad bots: rtou.ch/2c5cPmx.
The document discusses Cross Site Request Forgery (CSRF) attacks. It defines CSRF as an attack where unauthorized commands are transmitted from a user that a website trusts. The attack forces a logged-in user's browser to send requests, including session cookies, to a vulnerable website. This allows the attacker to generate requests the site thinks are from the user. The document outlines how CSRF works, example attacks, defenses for users and applications, and myths about CSRF. It recommends using unpredictable CSRF tokens or re-authentication to prevent CSRF vulnerabilities.
Verizon DMS' Bot Mitigation from Paul HobbsPaul Hobbs
The Verizon bot-mitigation solution helped StubHub identify and block bots performing scraping and fraud, which helped reduce transaction fraud and account takeovers. The solution uses device fingerprinting and behavioral analysis to detect and block 99.9% of malicious bots without impacting legitimate users. Verizon provides a dedicated security team and access to a database of known violators to help customers stay protected from emerging bot threats.
Vices & Devices - How IoT & Insecure APIs Became the New Cyber BattlefrontOry Segal
1. APIs have seen huge growth in usage, with over 25% of all internet traffic now consisting of API calls, largely driven by mobile apps and the growing IoT ecosystem.
2. Attackers have shifted focus to targeting APIs due to their simplicity and accessibility, exploiting common vulnerabilities like credential stuffing and application layer attacks against APIs developed with modern lightweight frameworks.
3. One campaign analyzed by Akamai showed attackers attempting 4 times as many stolen credentials through APIs compared to standard web logins, using over 4 times as many unique IP addresses per API-based campaign.
4. The rise of IoT devices has introduced new attack vectors, with credential abuse campaigns now exploiting vulnerable IoT devices like routers
Countering mobile malware in CSP’s network. Android honeypot as anti-fraud so...Denis Gorchakov
Honeypot is used for botnet analysis, traffic capturing and revealing C&C hostnames. It’s also used for detecting subscribers with infected devices and monitoring malware activities like funds withdrawal and remote control.
PHP is one of the most commonly used languages to develop web sites because of i
ts simplicity, easy to
learn and it can be easily embedded with any of the databases. A web developer with his basic knowledge
developing an application without practising secure guidelines, improper validation of user inputs leads to
various source code
v
ulnerabilities. Logical flaws while designing, implementing and hosting the web
application causes work flow deviation attacks.
In this paper, we are analyzing the complete behaviour of a
web application through static and dynamic analysis methodologies
State of the Art Analysis Approach for Identification of the Malignant URLsIOSRjournaljce
Malicious URLs have been universally used to ascend various cyber attacks including spamming, phishing and malware. Malware, short term for malicious software, is software which is developed to penetrate computers in a network without the user’s permission or notification. Existing methods typically detect malicious URLs of a single attack type. Hence such detection systems are failed to protect the users from various attacks. Malware spreading widely throughout the area of network as consequence of this it becomes predicament in distributed computer and network systems. Malicious links are the place of origin of all attacks which circulated all over the web. Hence malicious URLs should be detected for the prevention of users from these malware attacks. In this paper we described a novel approach which analyze all types of attacks by identifying malicious URLs and secure the web users from them. This technique prevents the users from malignant URLs before visiting them. Therefore efficiency of web security gets maintained. For such anatomization we developed an analyzer which identifies URLs and examine as malicious or benign. We also developed five processes which crawl for suspicious URLs. This approach will prevent the users from all types of attacks and increase efficiency of web crawling phase.
CEH v11 will teach you the latest commercial-grade hacking tools. Highlights of what sets CEH v11 apart from others are given in this SlideShare.
To learn more about CEH v11, click here: https://www.eccouncil.org/programs/certified-ethical-hacker-ceh/
Ensuring Property Portal Listing Data SecurityDistil Networks
Securing your property portal listing data is harder than ever. Why? Web scraping is cheap and easy. Bots simply steal whatever content they’ve been programmed to fetch – listing text, photos, and other data that should only be available to paid subscribers and legitimate consumers.
Review this presentation to learn how to avoid expensive litigation by protecting your content before the theft occurs. Review the latest research on how non-human traffic has evolved over the past few years and best practices to protect both copyrighted and non-copyrightable content.
Hear the results from research conducted with property portal executives on the current state of anti-scraping efforts.
This document proposes a web content analytics architecture to detect malicious JavaScript through real-time analysis of web traffic. It collects HTTP traffic using a proxy server and analyzes web content through static and dynamic analysis. Static analysis includes pattern matching, and dynamic analysis executes scripts to extract API call traces. Traces are clustered and signatures are generated by combining common tokens to detect similar malicious scripts while reducing false positives. The proposed approach analyzes JavaScript obfuscation and HTML5 usage to determine if further dynamic analysis is needed, and refines signatures through comparison to benign scripts. Evaluation showed the refined signatures improved detection rates while reducing false positives.
Distil Network Sponsor Presentation at the Property Portal Watch Conference -...Property Portal Watch
This document discusses ensuring security of property portal listing data from web scraping. It begins by defining web scraping as the automated copying of large amounts of data from websites. While some scraping is acceptable, malicious scraping can result in the theft of intellectual property like pricing, content, images and proprietary data from real estate portals. This damages brands through inaccurate data presentation and SEO impacts. The document notes that the cost of scraping has decreased while bot sophistication has increased, posing a growing problem for portals. However, most portals rely on outdated tools like IP blocking to address scraping that modern bots easily evade. Effective defenses require techniques like device fingerprinting and behavioral analysis. The session aims to help portals avoid expensive litigation by securing
Script based malware detection in online bankingJakub Kałużny
Online banking applications are particularly exposed to malware attacks. In order to prevent stealing from customer accounts, banks have invested in malware detection mechanisms. These programs are not installed on clients’ computers but rather implemented server-side or by including some JavaScript code on protected websites. We have tested such solutions which are using different detection methods. To name a few:
behavioral patterns,
web injects signatures,
user input analysis.
Our research points out clearly that even products sold as a „100% malware proof solutions” have serious implementation errors and it is only a matter of time when malware creators start targeting their guns against these vulnerabilities, effectively bypassing or abusing these countermeasures. Is it a road to failure or is there still time to improve these solutions? In this document we present security analysis of those solutions from attacker point of view and recommendations for improvement.
See also our presentation from Black Hat Asia and Confidence: „Bypassing malware detection mechanisms in online banking„
Nullcon Goa 2016 - Automated Mobile Application Security Testing with Mobile ...Ajin Abraham
Mobile Security Framework (MobSF) is an intelligent, all-in-one open source mobile application (Android/iOS) automated pen-testing framework capable of performing static and dynamic analysis. It can be used for effective and fast security analysis of Android and iOS Applications and supports both binaries (APK & IPA) and zipped source code. MobSF can also perform Web API Security testing with it's API Fuzzer that can do Information Gathering, analyze Security Headers, identify Mobile API specific vulnerabilities like XXE, SSRF, Path Traversal, IDOR, and other logical issues related to Session and API Rate Limiting.
Recognising Behavioural Patterns of Web API Bots Using Machine Learning Techn...Ravindra Guntur
Discovering bots that automate attacks and perform malicious actions is a key area of cyber security research. In this presentation we scope out the bot detection problem in the context of web API bots, and suggest how sequential neural network models can be used to solve the key problem of differentiating human behaviour from that of a malicious automaton.
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APIs are a wonderful thing and bring many benefits, but by their very nature they are also a window into how your business operates. If someone can exploit your system for gain, they will.
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DevCentral Technical Articles Bots mitigations overview with Advance WAF - Anti ... Options
Bots mitigations overview with Advance WAF - Anti Bot engine
Lior_Rotkovitch
F5 SIRT
on
27-Dec-2018 15:00
With more and more bots traffic hitting web applications it has become a necessity to manage bots
accessing web applications. To be able to manage bot access to your web application you must first be
able to detect them and only then allow or deny them.
Those actions can be done by F5 advance WAF and this article will provide an overview of bot mitigations
capabilities for versions 12.x , 13.x & 14.0
2. Advance WAF dos profile is a powerful bot management tool with various options to deal with bots. We
classify them into two main types:
1. Anomaly based detection – anomaly engine to identify increase in RPS generated by bots
2. Proactive bot defense – a dedicated anti bot engine to identify bot activity
Let’s review each one of them in more details.
Anomaly detection engine
Bot traffic most often generate increase in RPS. Advance WAF anomaly engine has several detection
mechanisms that identify an increase in traffic based on different criteria:
By source IP – detects increase of request per second which is the classical indication for a single bot
generating traffic from a given IP. “By source IP” measure ratio increase and fixed increase request per
second (RPS) from any IP accessing the web application.
The ratio RPS anomaly detection is the calculation of the past request per second in compare to the
current one. Ratio based should be used when the bot is originating from an already known IP that used to
send X amount of traffic and now send 2X or 3X times more traffic. The prevention policy will be activated
once this ratio per given source IP is reached.
The fixed RPS detection anomaly is the limit of request per second that above it will consider an attack and
will trigger the prevention policy. Fixed RPS detection should be used for new source IP’s with spikes that
pass the fixed threshold which above it considered to be an attack.
By Device ID – detect increase of RPS from a given device ID. The Device ID is the actual http agent that
generates the HTTP request which makes the source identification increase more accurate. The reason
Device ID exists is that the internet works with gateways also known as NATed traffic ( Network address
translation ) that represented by single IP with many devices behind it. Blocking the single source IP will
cause to blocking all legitimate users behind this source IP.
Similar to “by source IP “there are two anomaly types: ratio based and fixed rate which are calculated as
mentioned above.
It is recommended to use device ID with the source IP detection to isolate the attacking source behind a
source IP. Note that Device ID is done with java script injection, so check it before using it.
3. By geolocation - Sometimes the bot generates traffic from a specific country. This can be detected with
the geolocation detection that measure RPS arriving from a specific country.
It is recommended to use geolocation anomaly when traffic is not expected from those country with a low
fixed RPS rate.
By URL – detects increase of RPS on a specific URL which helps us determine if a bot is hitting the web
application but since it runs low and slow it is hard to detect the source IP.
It is recommended to use URL anomaly when by source IP / by Device ID can’t detect RPS increase due to
low and slow attack.
By site wide – detects increase on the entire web application (FQDN) Site wide detects RPS anomaly on
the entire virtual server (most often the app FQDN) and measures both source IP’s and URL’ to try and
conclude if there is an increase of traffic due to bots activity that are running under “the radar” without
being detect by other anomalies.
Each of the detection methods owns a prevention option that can apply to the detected source. This is
where the actual mitigation occurs to stop the attack. There are three prevention options available for each
of the detection that was introduce above:
4. Client Side Integrity Defense (CSID) aka browser challenge – is the pioneering Client side injection by
ASM (from 2008) to identify a browser or a bot. when a request arrive to the WAF DoS profile the request
is being held and a CSID script is send to the originating source. The script is a java script that checks if the
sources can:
Support JavaScript
Support HTTP cookie
Execute a computational challenge
CSID then sends the answer to the WAF DoS profile for evaluation that if qualify as a browser will be
allowed. Then the initial request that was held will be reconstruct and be sent to the web application. If the
answer from the CSID will not be qualify for the tests mention above then the initial request will be
dropped.
CAPTCHA is the second prevention policy option that each of the detection methods has. CAPTCHA is the
ultimate human or bot test and many web sites uses CATPCHA to challenge unknow sources that access
their app with it. The CAPTCHA challenge is present to the unknown source in the same way CSID, but
unlike CSID that is done under the hood with no user intervention, CAPTCHA is visible to the user. The
AWAF DoS profile CAPTCHA can be fine tune to fit the look and feel of the web site to get better usability.
Request blocking - Request blocking has two options:
Block all – any source that pass the detected thresholds will be blocked at the TCP IP level.
Rate limiting – any source that pass the detected thresholds will be rate limit to half the traffic or to the
historical RPS.
Note that block all will end the attack, so it should be use when we are sure that the source is indeed the
attacker. Rate limit on the other hand is slows down the attacker but will also allow other users to access
the app.
Those three preventions using different types of approaches: CSID is done with no user intervention while
CAPTHA is visible. CSID and CAPTCHA try to understand who the offending source is (bots or human) and
request limiting is indifferent to the “identity” and limits / blocks the offending sources.
Reporting
The Dos visibility (AVR module) provide visibility on the traffic that access your web application based on
the anomalies and mitigations that were triggered by the detections and prevention mention above. The
application event report provides details on the actions done by the dos profile and useful information can
be found such as: time of attack mitigations that were apply and additional information.
5. The graphs that are shown in the image below and located under Securtiy -> Reporting -> DoS -
> Dashboard
Anomaly Summary
The anomaly engine in the advance WAF dos profile is a TPS is a power full anti bot detection that can
identify bots activity by monitoring the amount of request on various entities such as by source Ip,
geolocation, specific URL , etc.
By source IP – detect increase in RPS on bots – use to detects bots
By Device ID - use to detects bots behind Nated IP sources
By URL - use to detects bots that focus on a single or fixed URL’s
By Geolocation - use to detects bots when they originate from a specific country
By Site wide – when the others detections don’t trigger but the site still experiencing load. (low and
slow attacks)
Once the anomaly engine identifies an increase in request the prevention policy is applied on the source
that triggered it. Client side integrity defense checks that the source is a browser and if not the source will
be blocked. CAPTCHA check is to identify a human and rate limit will slow down the source.
Client side integrity defense – use it when you want to allows only browsers to the site and no user
visibility to this check is needed.
CAPTCHA – use it when you want to evaluate a source for human or bot and user visibility to this
check is ok.
Block – rate limit – use it when you don’t want to block all the traffic from / to a specific source but
you do want to slow down the attack
6. Block – blocking - use it when you want to block the offending source and reset his connection.
Proactive bot defense
The second engine available in advance WAF is the anti bot engine which is also part of the ASM DoS
profile. The anti bot engine is a dedicated feature set for dealing with attack originating by bot and the
mitigations focus on the client side level of legitimacy.
Bot signatures
The first mitigation for bots is the bot signature mechanism that match user agent stings to detect known
bad bods. Bot signature includes two pre define signatures sets: benign and malicious which provides a
way to monitor the site bot traffic or to block unwanted bots.
Bots can be manage and allow specific bot to access the site with or without reporting and to report an
block the bot. the pre define bot signature should be used to understand the bots traffic that access your
web site. During attack those signatures can be protect your site when they are triggered by offending
sources.
Custom bot signature can be created for specific bot traffic. Custom signatures can be written in simple
mode for quick usage or in in advance mode that allows writing of more granular signatures Manual for bot
signatures.
For example, identifying a specific user agent on offending source which is not in the bot signatures list.
Adding the user agent to the bot signature pool will prevent the attack from this bot.
Anti bot Impersonating
Advance WAF also has a powerful mechanism that validated user agents stings to prevent from bad bot to
impersonate as good bots. Since user agent can be easily forged good bots includes domain name to
verify who they claim to be by issuing a reverse DNS look up.
for example: Googlebot/2.1 (+http://www.google.com/bot.html)
7. Since google is a good bot it should be allowed based on the user agent. However, only when doing a
reverse DNS check on the user agent FQDN can know for sure that this is truly google bot arriving from its
known IP as expected.
This configuration prevents most of the unwanted bots and improve application performance as various
reports claim to see around 50 % of the application traffic are bots. This anti Impersonating bot engine can
reduce the amount of bots traffic to the web application and is considered today as best practice.
To use the anti bot impersonating engine the DNS resolver and DNS look up list must be defined
Anti bots capability checks
Bots can be of various types and sometimes the only way to detect them is by inspecting their nature
which is what the Proactive bot defense does. The anti bot engine is a sophisticated set of checks that
has the following configuration:
This configuration makes the proactive bot defense easy to use and filter the bad bots. The concept of the
anti bot engine is to gradually inspect the source:
1. CSID – are you a browser that support cookie, Java script ?
2. Capabilities script – are you who you say you are ? comparing the browser answer to what the Anti
bot engine sees.
a. If the score is from 0 to 59 it is assumed to be a browser and the request can pass through.
8. b. If the score is between 60 to 99 it is declared unknown and a CAPTCHA is sent to unknown
sources. If the CAPTCHA challenge is solved the client is allowed in. A failed CAPTCHA
challenge results in a connection reset.
c. If the score is 100 then the request is reset
3. CAPTCHA – are you a human that can type characters ?
The configuration reflects those options:
If Block Suspicious Browsers is unchecked and CAPTCHA is unchecked à send CSID Challenge
If Block Suspicious Browsers is checked and CAPTCHA is checked à send Client Capabilities
challenge and give it a score:
If score is good, then allow access
If score in doubt send a CAPTCHA for human verification
If score is bad, then block it
If Block Suspicious Browsers is checked but CAPTCHA Challenge is unchecked à do not send
CAPTCHA and only block if the score is more than a human
Operation mode includes two modes:
Always – use it when under attack for immediate response to apply proactive bod defense on the entire
virtual server
e.g. the site is under DDoS and I want to mitigate all bots traffic now.
During attack – use it when other detection is triggered, and then proactive bot defense will be applied.
e.g. the site is not under attack and I want to mitigate with proactive bot defense only when any
other anomaly engine (mention above) is triggered in transparent mode. Or any request that pass
the rate limit of the anomaly engine.
The option for during attack provides a very powerful mitigation scenario where when the site is
experiencing increase in RPS that indicates bots activity only then examine the sources and if they are
suspicious present to those specific sources CAPTCHA challenge or block them if they are being detected
by capability script as bots.
The configuration will be as follows:
1. Define fixed thresholds for RPS on the anomaly engine in transparent mode
2. Define proactive bot defense to be during attack
9. a. Enable If Block Suspicious Browsers
b. Enable CAPTCHA Challenge
White listing
It is recommended to white list all known Ip’s that access the site and exclude them from the dos profile
checks. The reason is that when under attack the mitigations will not apply on known good sources.
Reporting
Bot defense reporting provides a full overview on the bots (good and bad) that access your web
application. Those graphs are critical when under attack to indicate the offending sources and easily
mitigate the attacks.
10. Irule mitigations
Irule are the F5 swiss army knife that can be used with the anti bot engine. In the following example any
source that access the login php URL will get the proactive bot defense check and be allowed if it pass it.
The full commands for using bot defnse with irule is located here: BotDefense
# EXAMPLE: enable client-side challenges on a specific URL
when BOTDEFENSE_REQUEST {
if {[HTTP::uri] eq "/login.php"} {
BOTDEFENSE::cs_allowed true
}
}
Proactive Bot defense Summary
Proactive bot defense is a dedicated bot detection and mitigations engine which focus on the attack agent
capabilities. There are several layers of protection with proactive bot defense :
Bot signature – is this known bad / good bod ?
Bot impersonation checks – is this a valid bot ?
Browser check – is this a browser ?
Browsers capabilities – which capabilities the browser has compare to what he say
CAPTCHA – is this a human ?
Proactive bot defense can be used with the anomaly engine the can trigger proactive bot defense once a
specific threshold has reached.
For example: only if login URL exceeds 20 RPS then apply proactive bot defense. (in transparent
mode)
Other combinations are also very useful when under attack.
11. For example: sending the client capabilities script and send CATPCHA to verify if the sources is a
browser and if this is a human.
Proactive bot defense has good reporting that allows fine tuning of the security policy to match bots traffic.
Finally irule can be used to utilize proactive bot defense.
Under Attack – use F5 SIRT
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