Papers and Reports

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Date	Name	INFO	CATEGORY	SUBCATE
6.9.26	REVSTEALER ramps up	Elastic Security Labs details emerging infostealer targeting gamers	PAPERS	MALWARE
27.8.26	GPUThor: Amplifying Rowhammer Attacks via Non-Uniform Patterns to Exploit ECC-Protected GPUs	GDDR memory in GPUs is vulnerable to Rowhammer attacks, where rapid memory accesses induce bit flips in adjacent cells,enabling data tampering and privilege escalation. However, prior GPU Rowhammer attacks trigger only tens to hundreds of bit flips,orders of magnitude fewer than CPU attacks, severely limiting their practical impact.	PAPERS	ATTACK
20.8.26	Bypassing Prompt Guards in Production with Controlled-Release Prompting	Ball et al. recently established that prompt filtering for AI alignment faces a fundamental barrier: under standard cryptographic assumptions, no filter running significantly faster than the protected model can universally distinguish adversarial prompts from benign ones.	PAPERS	AI
20.8.26	CDN Tsunami: Exploiting HTTP/3-HTTP/1.1 Conversion for DoS Attacks	Content Delivery Networks (CDNs) provide high availability, accelerate content delivery for their host websites, but are also vulnerable to different types of Denial-of-Service (DoS) attacks.	PAPERS	HACKING
19.8.26	AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems	Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multiagentecosystems, whose security properties remain largely unexplored.	PAPERS	MALWARE
19.8.26	PROMPT INFECTION: LLM-TO-LLM PROMPT INJECTION WITHIN MULTI-AGENT SYSTEMS	As Large Language Models (LLMs) grow increasingly powerful, multi-agent systems—where multiple LLMs collaborate to tackle complex tasks—are becoming more prevalent in modern AI applications. Most safety research, however, has focused on vulnerabilities in single-agent LLMs	PAPERS	AI
19.8.26	Thought Virus: Viral Misalignment via Subliminal Prompting in Multi-Agent Systems	Subliminal prompting is a phenomenon inwhich language models are biased towards certain concepts or traits through prompting with semantically unrelated tokens. While prior work has examined subliminal prompting in user-LLMinteractions, potential bias transfer in multi-agent systems and its associated security implications remain unexplored.	PAPERS	AI
19.8.26	Mind Viruses: Self-Propagating Ideas in Multi-Agent LLM Systems	AI agents are becoming more autonomous and increasingly interconnected, exposing them to new emergent risks arising from agent-to-agent interaction. One such risk is the spread of mind viruses: ideas or goals that propagate through multiagent systems by inducing the agents that adopt them to transmit them onward.	PAPERS	AI
31.7.26	Understanding Implicit Trust Errors in Core Carrier Networks through Multi-Agent Flaw Discovery and Analysis	Cellular core networks (CNs) are critical infrastructure, yet their internal security model has historically relied on physical isolation: interfaces between core components often operate within an assumed trust zone. As CNs transition to cloud-native deployments, this assumption weakens, expanding the attack surface and enabling external adversaries to reach previously internal interfaces.	PAPERS	VULNEREBILITY
29.7.26	CryptanalysisBench: Can LLMs do Cryptanalysis?	Cryptanalysis—the task of finding attacks against cryptographic schemes—sits at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced fastest.	PAPERS	AI
29.7.26	Cryptanalysis of 7-Round AES via the Algebraic Structure of its S-box	The AES S-Box is not a random permutation; we show that its algebraic structure allows for improved attacks on 7 rounds in the single-key setting. We focusour efforts on extending a 2 105 chosen plaintext and 2 99-time algorithm designed by	PAPERS	ATTACK
29.7.26	HAWK-n Key Recovery Reduces to SVP in Dimension n/2 + 1	HAWK is a lattice signature scheme that is currently a thirdround candidate in NIST’s post-quantum signature competition. We give an unconditional, deterministic polynomial-time reduction from HAWKn key recovery over Kn = Q(ζ2ℓ ) to poly(n) calls to an exact Shortest Vector Problem (SVP) oracle in dimension n/2 + 1, where n = 2ℓ−1 is the ring degree.	PAPERS	CRYPTO
29.7.26	HAWK: Having Automorphisms Weakens Key	The search rank-2 module Lattice Isomorphism Problem (smLIP), over a cyclotomic ring of degree a power of two, can be reduced to an instance of the Lattice Isomorphism Problem (LIP) of at most half the rank if an adversary knows a nontrivial automorphism of the underlying integer lattice.	PAPERS	CRYPTO
29.7.26	HAWK	HAWK is a signature scheme inspired by the introduction of the lattice isomorphism problem (LIP) to signatures [DvW22], and this specification document is based on the article that first described a practical variant [DPPvW22a].	PAPERS	CRYPTO
28.7.26	CyberGym-E2E: Scalable Real-World Benchmark for AI Agents’ End-to-End Cybersecurity Capabilities	AI has the potential to transform cybersecurity by enabling systems that can autonomously detect, analyze, and remediate software vulnerabilities. However, existing cybersecurity evaluations of AI systems are limited in scale or scope, and fail to capture the end-to-end lifecycle of real-world software vulnerability discovery and remediation	PAPERS	AI
28.7.26	CYBERGYM: EVALUATING AI AGENTS’ REAL-WORLD CYBERSECURITY CAPABILITIES AT SCALE	AI agents have significant potential to reshape cybersecurity, making a thorough assessment of their capabilities critical. However, existing evaluations fall short, because they are based on small-scale benchmarks and only measure static outcomes, failing to capture the full, dynamic range of real-world security challenges. To address these limitations, we introduce CyberGym, a large-scale benchmark	PAPERS	AI
22.7.26	ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?	AI agents are rapidly gaining capabilities that could significantly reshape cybersecurity, making rigorous evaluation urgent. A critical capability is exploitation: turning a vulnerability, which is not yet an attack, into a concrete security impact, such as unauthorized file access or code execution.	PAPERS	AI
10.7.26	Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting	The growing adoption of agentic LLM applicationshas introduced a new threat previously named as promptware.	PAPERS	BOTNET
8.7.26	The Promptware Kill Chain: How Prompt Injections Gradually Evolved Into a Multistep Malware Delivery Mechanism	Prompt injection was initially framed as the largelanguage model (LLM) analogue of SQL injection. However, over the past three years, attacks labeled as prompt injection have evolved from isolated input-manipulation exploits into multistep attack mechanisms that resemble malware.	PAPERS	AI
8.7.26	Git Hash Chain Malleability	Git commit signing is widely entrusted to serve as evidence that a commit hash uniquely and immutably identifies a specific piece of signed content. We show this invariant does not hold.	PAPERS	SECURITY
8.7.26	Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack	Large Language Models (LLMs) have risen significantly in popularity and are increasingly being adopted across multiple applications. These LLMs are heavily aligned to resist engaging in illegal or unethical topics as a means to avoid contributing to responsible AI harms.	PAPERS	AI
8.7.26	Smoke and Mirrors: Jailbreaking LLM-based Code Generation via Implicit Malicious Prompts	The proliferation of Large Language Models (LLMs) has revolutionized natural language processing and significantly impactedcode generation tasks, enhancing software development efficiency and productivity.	PAPERS	AI
8.7.26	RedCode: Risky Code Execution and Generation Benchmark for Code Agents	With the rapidly increasing capabilities and adoption of code agents for AI-assistedcoding and software development, safety and security concerns, such as generating or executing malicious code, have become significant barriers to the real-world deployment of these agents.	PAPERS	VULNEREBILITY
8.7.26	Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents	For safety reasons, large language models (LLMs) are trained to refuse harmful user instructions, such as assisting dangerous activities. We study an openquestion in this work: does the desired safety refusal, typically enforced in chat contexts, generalize to non-chat and agentic use cases?	PAPERS	AI
8.7.26	Refused in Chat, Written in Code: Workflow-Level Jailbreak Construction in IDE Coding Agents.	Large language models are increasingly deployed as IDE-integrated coding agents that decompose tasks, generate and edit files, run code, and refine outputs over many turns. Yet their safety is still often evaluated as if they were chatbots: one harmful prompt, one response, judged in isolation.	PAPERS	VULNEREBILITY
6.7.26	Reflecthernet: Exfiltrating 100BASE-TX Ethernet Traffic Using a Retroreflector Hardware Trojan	This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Electromagnetic eavesdropping is a well-established attack vector for remotely monitoring a target activity, most notably displays, over considerable ranges.	PAPERS	MALWARE
6.7.26	TEMPEST-LoRa: Cross-Technology Covert Communication	Electromagnetic (EM) covert channels pose significant threats to computer and communications security in air-gapped networks. Previous works exploit EM radiation from various components (e.g., video cables, memory buses, CPUs) to secretly send sensitive information.	PAPERS	ATTACK
6.7.26	TrojPix: Electromagnetic Covert Channels via Imperceptible Pixel Modulation	Air-gapped networks rely on physical isolation to prevent external connectivity. Prior electromagnetic (EM) covert channels have exploited emissions from video cables, memory buses, and CPUs, yet they rarely achieve high throughput, long range, and visual imperceptibility simultaneously, limiting practical utility in air-gapped settings.	PAPERS	ATTACK
30.6.26	Mind your key: An Empirical Study of LLM API Credential Leakage in iOS Apps	The rapid integration of large language models (LLMs) into mobileapplications has introduced a new class of credential security risk: leaked credentials that grant unauthorized access to LLM inference services, which can cause financial damage to the developer side. Prior work has studied credential leakage across various platforms, with a primary focus on Android Apps.	PAPERS	AI
30.6.26	LM-Scout: Analyzing the Security of Language Model Integration in Android Apps	Developers are increasingly integrating Language Models (LMs) into their mobile apps to provide features such as chat-based assistants. To prevent LM misuse, they impose various restrictions, including limits on the number of queries, input length, and allowed topics. However, if the LM integration is insecure, attackers can bypass these restrictions and gain unrestricted access to the LM, potentially harming developers’ reputations and leading to significant financial losses.	PAPERS	AI
30.6.26	Leaky Apps: Large-scale Analysis of Secrets Distributed inAndroid and iOS Apps	Mobile apps store various types of secrets to support their func-tionalities. These include API keys, and cryptographic material toauthenticate users and access backend services. Once distributed,attackers can reverse-engineer the apps, and these secrets becomeaccessible, posing risks such as data leaks, and service abuse	PAPERS	CRYPTO
30.6.26	On the (In)Security of LLM App Stores	LLM app stores have seen rapid growth, leading tothe proliferation of numerous custom LLM apps. However, this expansion raises security concerns. In this study, we propose a three-layer concern framework to identify the potential security risks of LLM apps, i.e., LLM apps with abusive potential, LLM apps with malicious intent, and LLM apps with exploitable vulnerabilities.	PAPERS	AI
30.6.26	Protocol Prying: Systematic Vulnerability Research in the Apple AirDrop and Android Quick Share Proximity Transfer Protocols	Apple AirDrop and Google/Samsung Quick Share are proximity file-transfer protocols used by over five billion devices, yet their application-layer security properties remain largelyunstudied because both stacks are proprietary and undocumented	PAPERS	ATTACK
22.6.26	Squidbleed (CVE-2026-47729)	Meet Squidbleed: a Heartbleed-style vulnerability that leaks internal memory from every version of Squid Proxy, in its default configuration.	PAPERS	VULNEREBILITY
20.6.26	Introducing usbliter8	An A12/A13 SecureROM exploit	PAPERS	EXPLOIT
9.6.26	FROST ATTACK	FROST: Fingerprinting Remotely using OPFS-based SSD Timing	PAPERS	ATTACK
6.6.26	Patch-to-PoC: A Systematic Study of Agentic LLM Systems for Linux Kernel N-Day Reproduction	Autonomous large language model (LLM) based systems have recently shown promising results across a range of cybersecurity tasks. However, there is no systematic study on their effectiveness in autonomously reproducing Linux kernel vulnerabilities with concrete proofs-of-concept (PoCs).	PAPERS	VULNEREBILITY
20.5.26	StopRansomware Guide	Ransomware is a form of malware designed to encrypt files on a device, rendering them and the systems that rely on them unusable. Malicious actors then demand ransom in exchange for decryption.	PAPERS	RANSOMWARE
20.5.26	SOFTWARE BILL OF MATERIALS FOR AI	Accessing information on the supply chain of an artificial intelligence (AI) system, as well as its individual components and dependencies, is critical to strengthen cybersecurity of AI. Transparency and knowledge about AI system composition fosters vulnerability management and supports cybersecurity risk management.	PAPERS	AI
3.5.26	Linux Kernel Runtime Guard (LKRG) 1.0	Linux Kernel Runtime Guard (LKRG) is a Linux kernel module that performs runtime integrity checking of the kernel and detection of security vulnerability exploits against the kernel, prevention of and response to successful attacks, and encrypted remote logging.	PAPERS	VULNEREBILITY
3.5.26	Password cracking: past, present, future	Passwords (or phrases) remain a distinct and ubiquitous authentication factor. They are also widely used to derive encryption keys for data or other keys. Password cracking is used in security audits, penetration testing, to recover or gain access to data, keys, or funds, and for a variety of other purposes.	PAPERS	HACKING
3.5.26	Linux kernel remote logging: approaches, challenges, implementation	This talk is based on research conducted for our Linux Kernel Runtime Guard (LKRG) project, which is a Linux kernel module that performs runtime integrity checking of the kernel and detection of security vulnerability exploits against the kernel.	PAPERS	VULNEREBILITY
3.5.26	15+ years of oss-security	These are the slides of Solar Designer's SSTIC 2023 keynote talk with minor revisions as later presented at BSidesLjubljana 2023.	PAPERS
3.5.26	Linux Kernel Runtime Guard (LKRG) in a nutshell	These are the slides on LKRG that we used at OSTconf 2020. This presentation is an update of LKRG under the hood (CONFidence 2018).	PAPERS	VULNEREBILITY
3.5.26	Linux Kernel Runtime Guard (LKRG) under the hood	These are the slides on LKRG that we used at CONFidence 2018. This presentation is updated by LKRG in a nutshell (OSTconf 2020), so you might want to check that one out as well.	PAPERS	VULNEREBILITY
3.5.26	Haswell metaprogramming	Haswell is an Intel CPU microarchitecture introduced to market in 2013 with CPUs such as Core i7-4770K (which we used for the testing mentioned on slide 3). The information on these slides should also apply to Intel's newer CPUs at least through the end of 2019.	PAPERS	VULNEREBILITY
3.5.26	yescrypt: large-scale password hashing	These are the slides on yescrypt that we used at BSidesLjubljana 2017. In a sense, this presentation is a continuation of Password security: past, present, future (PHDays 2012, Passwords^12), Password hashing at scale (YaC 2012), New developments in password hashing: ROM-port-hard functions (ZeroNights 2012), and yescrypt	PAPERS	VULNEREBILITY
3.5.26	john-devkit: specialized compiler for hash cracking	These are the slides we used for a lightning talk at PHDays 2015, and here's the corresponding GitHub project. Aleksey also gave a follow-up talk at PHDays 2016.	PAPERS	SECURITY
3.5.26	Is infosec a game?	You can play the game online in recent web browsers on fast CPUs (we use JsDOSBox) or offline in DOSBox (which works perfectly even on slower CPUs) or on bare metal (e.g. by adding it into a FreeDOS image). To obtain a copy for offline play, simply unzip the PDF file below (yes, you read this right).	PAPERS	HACKING
3.5.26	Energy-efficient bcrypt cracking	These are the slides we used at PasswordsCon Las Vegas 2014 (colocated with BSidesLV), Skytalks 2014 (colocated with DEFCON), and FSEC 2014. We used a much older version of these slides at PasswordsCon Bergen 2013.	PAPERS	HACKING
3.5.26	yescrypt: password hashing scalable beyond bcrypt and scrypt	These are the slides on yescrypt that we used at PHDays 2014. In a sense, this presentation is a continuation of Password security: past, present, future (PHDays 2012, Passwords^12), Password hashing at scale (YaC 2012), New developments in password hashing: ROM-port-hard functions (ZeroNights 2012), and it is continued with yescrypt: large-scale password hashing (BSidesLjubljana 2017), so please check those out as well.	PAPERS	SECURITY
3.5.26	Looking inside the (Drop) box	These are the slides we used at NordU2002, CanSecWest / core02, and FOSDEM 2003 (with updates). (A Polish translation was also used at Open Source Security 2005.)	PAPERS	SECURITY
3.5.26	Distributable probabilistic candidate password generators	These are the slides we used at Passwords^12. You might also want to see Automatic wordlists mangling rules generation, also presented by Simon at Passwords^12.	PAPERS	SECURITY
3.5.26	Automatic wordlists mangling rules generation	These are the slides we used at Passwords^12. You might also want to see Distributable probabilistic candidate password generators, also presented by Simon at Passwords^12.	PAPERS	SECURITY
3.5.26	New developments in password hashing: ROM-port-hard functions	These are the slides we used at ZeroNights 2012. In a sense, this presentation is a continuation of Password security: past, present, future (PHDays 2012, Passwords^12) and Password hashing at scale (YaC 2012), and it is continued with yescrypt: password hashing scalable beyond bcrypt and scrypt (PHDays 2014), so please check those out as well.	PAPERS	CRYPTO
3.5.26	Password hashing at scale	These are the slides we used at YaC 2012. In a sense, this presentation is a continuation of Password security: past, present, future (PHDays 2012, Passwords^12) and it is continued with New developments in password hashing: ROM-port-hard functions (ZeroNights 2012) and yescrypt: password hashing scalable beyond bcrypt and scrypt (PHDays 2014), so please check those out as well.	PAPERS	CRYPTO
3.5.26	Password security: past, present, future	These are the slides we used at PHDays 2012 and Passwords^12 (with major updates). In a sense, this presentation is continued with Password hashing at scale (YaC 2012) and New developments in password hashing: ROM-port-hard functions (ZeroNights 2012), so please check those out as well, although the most relevant material from them has been merged into the Passwords^12 revision of this presentation.	PAPERS	CRYPTO
3.5.26	IPv6: What, Why, How		PAPERS	SECURITY
3.5.26	Openwall GNU/*/Linux	This presentation/tutorial by Jen "Furry" Linkova introduces those familiar with IPv4 to IPv6. It covers both "executive" and highly technical topics, with slight bias on security and privacy.	PAPERS	SECURITY
3.5.26	SSH Traffic Analysis	These are the slides we used at HAL2001 and NordU2002 (with updates).	PAPERS	SECURITY
28.4.26	LEROBOT: AN OPEN-SOURCE LIBRARY FOR END-TO-END ROBOT LEARNING	Robotics is undergoing a significant transformation powered by advances in highlevel control techniques based on machine learning, giving rise to the field of robot learning.	PAPERS	SECURITY
26.4.26	GopherWhisper	GopherWhisper: A burrow full of malware	PAPERS	MALWARE
10.4.26	ESPIONAGE FOR REPRESSION: FORENSIC ANALYSIS OF A CROSS-BORDER HACK-FOR-HIRE CAMPAIGN TARGETING CIVIL SOCIETY IN MENA	ESPIONAGE FOR REPRESSION: FORENSIC ANALYSIS OF A CROSS-BORDER HACK-FOR-HIRE CAMPAIGN TARGETING CIVIL SOCIETY IN MENA	PAPERS	SECURITY
8.4.26	GeForge: Hammering GDDR Memory to Forge GPU Page Tables for Fun and Profit	Over the years, Rowhammer has been leveraged to mount a wide range of attacks against system main memory.	PAPERS	ATTACK
8.4.26	GDDRHammer: Greatly Disturbing DRAM Rows — Cross-Component Rowhammer Attacks from Modern GPUs	While Rowhammer has been extensively studied in CPU-based memory systems, a very recent work by Lin etal. (USENIX Security ‘25) extended this line of research to GDDR6 GPU memory, demonstrating the first Rowhammer bit flips on NVIDIA GPUs	PAPERS	ATTACK
8.4.26	GPUHammer: Rowhammer Attacks on GPU Memories are Practical	Rowhammer is a read disturbance vulnerability in modern DRAM that causes bit-flips, compromising security and reliability.	PAPERS	ATTACK
17.2.26	Zero Knowledge (About) Encryption: A Comparative Security Analysis of Three Cloud-based Password Managers	Zero Knowledge Encryption is a term widely used by vendors of cloud-based password managers. Although it has no strict technical meaning, the term conveys the idea that the server, who stores encrypted password vaults on behalf of users, is unable to learn anything about the contents of those vaults.	PAPERS	CRYPTO
5.2.26	The Trigger in the Haystack: Extracting and Reconstructing LLM Backdoor Triggers	Detecting whether a model has been poisoned is a longstanding problem in AI security. In this work, we present a practical scanner for identifying sleeper agent-style backdoors in causal language models.	PAPERS	AI
23.1.26	Ransomware 2026	New Actors and Threats Emerge as the Threat Landscape Evolves	PAPERS	RANSOMWARE
19.1.26	StackWarp: Breaking AMD SEV-SNP Integrity via Deterministic Stack-Pointer Manipulation through the CPU’s Stack Engine	Confidential Virtual Machines (CVMs), such as AMD SEVSNP, aim to protect guest operating systems from an untrusted host by encrypting state and constraining privileged control. These platforms promise isolation even in multi-tenant cloud setups where simultaneous multithreading (SMT) remains enabled	PAPERS	ATTACK