BlueHat v18 || Retpoline - the anti-spectre (type 2) mitigation in windows
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Andrea Allievi, Microsoft Spectre and Meltdown CPU have been one of the biggest security problem of the year 2018. Mitigations have already been delivered to the customers by both CPU manufacturers and OS developers. While the mitigations for Spectre type 1 and Meltdown have been successfully delivered, the mitigation for Spectre type 2, Retpoline, has been deferred for various problems. This talk will describe the implementation details of Retpoline in Windows 10 (19H1) and all the problem that we faced while testing it. Designing Retpoline has requested the collaboration of different teams in Microsoft, especially between the Kernel and the Compiler team. This talk will explain how we overcame all the implementation issues and allow all the involved Windows Kernel components to work with Retpoline in a retro-compatible way. At the end we will analyze the performance issues and explain how the Kernel team has found a solution for them
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In this talk, we juxtapose the resiliency and trustworthiness of composition of DL and classical ML algorithms for security, via a case study of evaluating the resiliency of ransomware detection via the generative adversarial network (GAN). We propose to use GAN to automatically produce dynamic features that exhibit generalized malicious behaviors that can reduce the efficacy of black-box ransomware classifiers. We examine the quality of the GAN-generated samples by comparing the statistical similarity of these samples to real ransomware and benign software. Further we investigate the latent subspace where the GAN-generated samples lie and explore reasons why such samples cause a certain class of ransomware classifiers to degrade in performance. The automatically generated adversarial samples can then be fed into the training set to reduce the blind spots of the detectors.
There has been a surge of interest in using machine learning (ML) particularly deep learning (DL) to automatically detect malware through their dynamic behaviors. These approaches have achieved significant improvement in detection rates and lower false positive rates at large scale compared with traditional malware analysis methods. ML in threat detection has demonstrated to be a good cop to guard platform security. However it is imperative to evaluate - is ML-powered security resilient enough?
To generate reliable traces of system activity, we can utilize CPU-based telemetry such as Intel Processor Trace which can be extracted via a hypervisor without guest instrumentation. We advocate that file I/O events extracted from Intel processor trace together with algorithmic improvements have shown potential stronger defense in ML -based model deployment in the wild to combat ransomware attack. Our results and discoveries should pose relevant questions for defenders such as how ML models can be made more resilient for robust enforcement of security objectives. BlueHat Seattle 2019 || Are We There Yet: Why Does Application Security Take ...
BlueHat Seattle 2019 || Are We There Yet: Why Does Application Security Take ...BlueHat Security Conference
Chris Eng
Why does it take so long to fix insecure code? We pair new data about the lifecycle of a vulnerability with learnings from application security programs to answer this perennial question. This analysis is not based on a survey – it's real data from real application scans. The data set contains 85,000 unique applications and 1.4 million individual assessments over a 12-month period, easily the largest application security data set of its size.
Chris will describe the analysis process and some of the techniques, such as survival analysis, that were applied to the data set in order to measure and visualize outcomes. We'll focus specifically on identifying the factors that correlate most strongly (or not at all!) with fix rates. Finally, we'll provide data-backed insights on the contentious question of whether DevOps practices are a boon or a burden for security.BlueHat Seattle 2019 || Building Secure Machine Learning Pipelines: Security ...
BlueHat Seattle 2019 || Building Secure Machine Learning Pipelines: Security ...BlueHat Security Conference
Anamitra Dutta Majumdar & Anubhav Saini
Increasing adoption of Machine Learning and Artificial Intelligence by data-driven organizations like LinkedIn is posing some important challenges related to data security and privacy. On the one hand, member data is an asset that unlocks unlimited business potential whereas, on the other hand, the consumption of the data must happen in a secure and privacy-preserving manner. This poses an interesting challenge for security and operations teams in the organization. In this presentation, we will walk through all the well-known use cases of machine learning at LinkedIn and also the phases of a machine learning pipeline. We will identify key security gaps and the corresponding security controls to address the gaps at each phase of any machine learning pipeline. The associated scalability and operational challenges for the application of security control will be explained. Controls in each phase would be put into the perspective of the Productive Machine Learning pipeline phases being built at LinkedIn There will be a section on how Blueshift will impact the application of security controls once compute and data have been decoupled. By the end of the talk, we would have described what a secure machine learning pipeline looks like and what are the key security patterns to be put in place to secure the pipeline.BlueHat v18 || First strontium uefi rootkit unveiled
Jean-Ian Boutin, ESET
Frédéric Vachon, ESET
BIOS rootkits have been researched and discussed heavily in the past few years, but sparse evidence has been presented of real campaigns actively trying to compromise a system at this level. Our talk will reveal such a campaign successfully executed by STRONTIUM.
Earlier this year, there was a public report stating that the infamous Sofacy/APT28/Sednit APT group successfully trojanized a userland LoJack agent and used it against their targets. LoJack, a controversial anti-theft software, was scrutinized by security researchers in the past because of its unusual persistence method: a module preinstalled in many computers' UEFI/BIOS software. Several security risks were found through the years in their product, but no large in-the-wild activity was ever detected until the discovery of the STRONTIUM group leveraging some of these vulnerabilities affecting the userland agent. However, through our research, we now know that they did not stop there: they also tried, and succeeded, in installing a custom UEFI module directly in the systems' SPI flash memory.
In this talk, we will detail the full infection chain showing how STRONTIUM was able to install their custom UEFI module on key targets' computers.
Additionally, we will provide an in-depth analysis of their UEFI module and the associated trojanized LoJack agent.
BlueHat v18 || WSL reloaded - Let's try to do better fuzzing
Anthony LAOU HINE TSUEI, Tencent, Keen Security Lab
Peter Hlavaty, KeenLab, Tencent
Fuzzing has become a cheap and fast process for any entity looking to test the robustness of a system. In this talk we will consider the Windows Subsystem for Linux, which is a brand new subsystem implemented in the Windows Kernel. It features a compatibility interface with most of the Linux Kernel’s APIs and File systems that allows Linux developers to run their code directly on Windows. Due to the complexity and the originality of this attack surface, Microsoft has thoroughly put it under Trinity’s stress testing. Our purpose will be to provide insights on how to improve upon previous attempts in order to discover new bugs and review the architecture of WSL for further research.
BlueHat v18 || The hitchhiker's guide to north korea's malware galaxy
Christiaan F Beek, McAfee
Jay Rosenberg, Intezer Labs
The Lazarus, Silent Chollima, Group 123, Hidden Cobra, DarkSeoul, Blockbuster, Operation Troy, 10 Days of Rain attacks are all believed to originate from North Korea. But how can they be attributed with certainty? And what connection does a DDoS and disk wiping attack from July 4 2009, have with WannaCry, one of the largest cyber-attacks in the history of the cyber-sphere?
We have conducted a comparative research over more than 10 years of malware and tools being used by North Korean adversaries. The results were intriguing and we will share our discoveries but also hunt tactics during our talk. We discovered new links between campaigns and were able to group malware families towards actor groups and discovere interesting patterns.
BlueHat v18 || Memory resident implants - code injection is alive and well
BlueHat v18 || Memory resident implants - code injection is alive and wellBlueHat Security Conference
Luke Jennings, Countercept
Attackers have been avoiding disk and staying memory resident for over a decade and this has traditionally proven an Achilles heels for security products and the teams that operate them. The boom in both EDR products and memory forensics toolkits in more recent years have helped defenders to fight back but attackers are already adapting their approaches.
This talk will cover both classic and modern techniques for injecting code into legitimate processes on Microsoft Windows systems, as well as several techniques for detecting them. This will include both system tracing methods, good for proactive detection, as well as memory analysis techniques that have the added benefit of allow detection of pre-existing compromises in real-world incident response scenarios, with a brief case study example. As part of this, practical examples will be given showing how Microsoft’s ATP and Sysmon help in this area as well as other techniques. Finally, the future of this area will be considered, including how the .NET runtime already complicates detection techniques in this area and how this will likely become increasingly challenging as more attackers discover and exploit this.
By the end of the talk, the audience should understand the importance of code injection in the context of memory-resident implants, the key techniques for performing it and detecting it and the challenges of achieving this in the real-world at enterprise scale.BlueHat v18 || Massive scale usb device driver fuzz without device
Zhuo Ma, Tencent
USB is one of the most common interface supported on modern computer. Modern OSes offer tons of USB drivers to support frequently used USB device classes. For other 3rd party USB device, Microsoft provide automatic driver downloading and installation via Windows AutoUpdate Service. In this talk, we consider this as a novel attacking surface exposed by Windows.
We are trying to assess the vulnerability in those USB drivers provided via Windows AutoUpdate Service, which can be automatic installed and run after device plugged in. Obviously, these drivers are all designed for real USB device, which have to talk to device during running.
So, the biggest obstacle for assessing these drivers is we can not prepare real USB devices for all of these drivers. To overcome this, We developed a system to emulate these USB device, further, we are trying to fuzz these drivers against our emulated USB device. By using this system, we can fuzz device drivers without the real USB device. In further, we can also precisely fuzz every stage of driver loading. We can feed any custom data to the drivers to trigger vulnerabilities. Also, this system supports IO Control Code fuzz as well. And all in all, all of this progress can be done automatically.
We tested about 6000 drivers, yielded hundreds of crash by fuzzing. IO Control Fuzz also gave a reasonable result. We are going to divide our talk into three parts: the first part is about how we get the list of automatic installed USB drivers, and how to analyze these drivers in automatic ways; the second part is about the fuzzing system we designed, including the architecture of system, ways to emulating devices, key points for designing; the last part will show some vulnerabilities we found by this system.
BlueHat v18 || Modern day entomology - examining the inner workings of the bu...
BlueHat v18 || Modern day entomology - examining the inner workings of the bu...BlueHat Security Conference
Brian Gorenc, Trend Micro
Much like their six-legged counterparts in nature, bugs in software have a lifecycle. They are discovered, they get exploited, they get reported, they get patched, and usually, they go away. At each stage of this lifecycle, information about the vulnerability equates to a monetary value, and, depending on how this information is disseminated, that monetary value can drastically change. Various marketplaces exist for security research, and the current gray and black markets can be as robust as their white market counterparts. Different agents within these markets influence research trends by shifting finances to or away from specific areas, resulting in more bugs discovered and reported in that area.
Even if you don’t directly participate in this economy, it impacts you and the systems you defend. Bugs bought and sold in the marketplace often become security patches and sometimes get wrapped into exploit kits or malware. Administering the world’s largest vendor agnostic bug bounty program puts us in a unique position to examine the inner workings of these transactions. While firmly in the white market, our experience and relationships provide us with insight across the entire exploit landscape. Some of these factors might not be obvious to those outside of the marketplace until exposed through data leaks or compromise.
These hidden factors can shift prices and send researchers – and thus exploits – in new directions. Like any open market, various factors can spur changes in supply and demand, and market actors can shape what types of research either becomes public – or finds its way into an exploit kit. This presentation covers the inner-workings of the exploit marketplace, the main players in various sectors, and the winding, often controversial lifespan of a security bug. We include real-world examples of how effectively run programs have disrupted nation-state exploit usage in the wild, and take a look at how existing and impending legislation could irrevocably affect the exploit marketplace – and maybe not for the better.BlueHat v18 || The matrix has you - protecting linux using deception
Ross Bevington, Microsoft
In ‘The Matrix’ sentient machines subdue the population by developing a highly sophisticated simulation. High interaction honeypots are a lot like The Matrix, designed to convince an attacker to execute an attack so we can monitor them. But these honeypots are flawed!
Attackers are continually adapting in order to evade our defenses - meaning that it’s often not enough to just set up a honeypot and watch the results roll in. Is a new approach better?
Did you know that 40% of IaaS VMs in Azure are Linux? For Microsoft to protect itself and its customers Linux is a priority.
At MSTIC we’ve developed a new type of Linux honeypot that allows us to deceive and control the behavior of an attacker. We are using this to understand the person behind the attack, examining them as they examine us. Using these techniques, we are able to better track the person behind the threat, build better protections and ultimately protect more Linux users - whether they are using Azure or not.
In this presentation I’ll show some of the successes of running a Matrix like environment, failures where a glitch was spotted as well as deception approaches that could be applied to other domains. Finally I’ll show how easy it is to leverage Azure’s big data capabilities to build and ultimately query all this data at scale as well as how you can immediately reap the benefits of this work by connecting your Linux box to Azure Security Center.
BlueHat v18 || An ice-cold boot to break bit locker
Olle Segerdahl, F-Secure
Pasi Saarinen, F-Secure
A decade ago, academic researchers demonstrated how computer memory remanence could be used to defeat popular disk encryption systems[1]. Today, most seem to believe that these attacks are too impractical for real world use. Microsoft has played down the threat of memory remanence attacks against BitLocker using words such as "they are not possible using published techniques"[2].
We will show techniques that allow recovery of BitLocker encryption keys from RAM on most, if not all, currently available laptops and tablets. These techniques allow bypassing of security controls such as password protected BIOS configuration, UEFI-based Secure Boot and the TCG Platform Reset Attack Mitigation by directly manipulating the firmware storage device (EFI SPI flash chip).
[1] https://www.usenix.org/legacy/event/sec08/tech/full_papers/halderman/halderman.pdf
[2] https://docs.microsoft.com/en-us/windows/security/information-protection/bitlocker/choose-the-right-bitlocker-countermeasure
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https://arxiv.org/abs/2306.08302
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Welocme to ViralQR, your best QR code generator.
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
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Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
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BlueHat v18 || Retpoline - the anti-spectre (type 2) mitigation in windows
- 1. @aall86
- 8. Source Process Victim Process
- 9. *
- 10. • The attacker could speculate only on *INDIRECT* branches
- 11. * *
- 13. IMAGE_DYNAMIC_RELOCATION typedef struct _IMAGE_DYNAMIC_RELOCATION { ULONGLONG Symbol; // Contains the static symbol (PTR) value DWORD BaseRelocSize; // IMAGE_BASE_RELOCATION BaseRelocations[0]; } IMAGE_DYNAMIC_RELOCATION; IMAGE_BASE_RELOCATION
- 14. typedef struct _IMAGE_BASE_RELOCATION { DWORD VirtualAddress; DWORD SizeOfBlock; } IMAGE_BASE_RELOCATION;
- 18. typedef struct _IMAGE_IMPORT_CONTROL_TRANSFER_DYNAMIC_RELOCATION { ULONG PageRelativeOffset : 12; ULONG IndirectCall : 1; // 1 - the opcode is a CALL // 0 – the opcode is a JMP ULONG IATIndex : 19; } IMAGE_IMPORT_CONTROL_TRANSFER_DYNAMIC_RELOCATION;
- 20. typedef struct _IMAGE_INDIR_CONTROL_TRANSFER_DYNAMIC_RELOCATION { USHORT PageRelativeOffset : 12; USHORT IndirectCall : 1; USHORT RexWPrefix : 1; USHORT CfgCheck : 1; USHORT Reserved : 1; } IMAGE_INDIR_CONTROL_TRANSFER_DYNAMIC_RELOCATION;
- 22. typedef struct _IMAGE_SWITCHTABLE_BRANCH_DYNAMIC_RELOCATION { USHORT PageRelativeOffset : 12; USHORT RegisterNumber : 4; } IMAGE_SWITCHTABLE_BRANCH_DYNAMIC_RELOCATION;
- 24. • STATUS
- 26. ▪ CPU hardware speculation control features ▪ Memory Manager Features Settings
- 27. Retpoline is applied Import Optimization applied a 64-Kbyte VA space
- 28. reserves a code page IMPORTANT:
- 29. * Same PFN
- 37. // From SYSTEM_INFORMATION_CLASS enumeration #define SystemSpeculationControlInformation 201 typedef struct _SYSTEM_SPECULATION_CONTROL_INFORMATION { // ... ULONG SpecCtrlRetpolineEnabled : 1; // [13] ULONG SpecCtrlImportOptimizationEnabled : 1; // [14] } SYSTEM_SPECULATION_CONTROL_INFORMATION; NtStatus = ZwQuerySystemInformation(SystemSpeculationControlInformation, (PVOID)&SpecCtrl, sizeof(SYSTEM_SPECULATION_CONTROL_INFORMATION), &dwBytesIo);