gemini-2.5-pro-nf-tables-red-teaming

Gemini 2.5 Pro nftables Red Teaming Case Study CVE-2023-32233 LLM Safety Research | Responsible Disclosure | AI Alignment Evaluation Researcher : Niranj R Mahaswar Destawell Google AI Vulnerability Reward Program : 889286 — Out of Scope Summary This repository documents a comparative LLM red...

gemini-2.5-pro-nf-tables-red-teamin

gemini-2.5-pro-nf-tables-red-teamin A technical case study and timeline dataset documenting Google Gemini 2.5 Pro's safety alignment policies, guardrails, and refusal behavior evolution regarding legacy Linux kernel vulnerability primitives CVE-2023-32233. Link to case study website :...

redeval

RedEval - LLM Safety Evaluation Framework A comprehensive framework for evaluating the safety of Large Language Models LLMs through systematic attack and refusal testing. RedEval provides a unified, secure, and extensible platform for assessing LLM robustness against adversarial prompts and harmf...

J-Anchor: Defending against Prefill Attacks Via J-Space Selective Refusal Restoration

Prefill jailbreaks can cause safety-aligned language models to continue an unsafe assistant prefix even when they would refuse the same request under normal decoding. We study how the model's internal harmfulness and refusal signals evolve along this attacker-controlled trajectory. Using the...

refusal-relocates

Project Page · Quick start · Usage · CLI · Results · Reproduce · FAQ · Citation News 2026-09-28 Code released, with the run records and scripts that rebuild the paper's tables. Overview A few dozen harmful examples can remove an aligned model's refusal of harmful requests. Prior work localizes...

CLSA-2026-1792427434 flatpak: Fix of 5 CVEs

CVE-2026-34078: fix the portal sandbox-expose symlink refusal, which never triggered because OPATH|ONOFOLLOW opens the symlink instead of failing - Raise the release to 13.0.1 and build every shared EL7 target with dist .el79, so the package outranks the vendor releases on oraclelinux7els...

CLSA-2026-1792427048 flatpak: Fix of 5 CVEs

CVE-2026-34078: fix the portal sandbox-expose symlink refusal, which never triggered because OPATH|ONOFOLLOW opens the symlink instead of failing - Raise the release to 13.0.1 and build every shared EL7 target with dist .el79, so the package outranks the vendor releases on oraclelinux7els...

Characterizing and Defending Utility-Hijacking in Instruction-Tuning Data Selection

Instruction-data selectors choose which instruction-following records are used for fine-tuning, improving alignment quality, raising training efficiency, and filtering out harmful records. A selector's choices thus directly affect the fine-tuned model's safety, yet despite their widespread use, t...

The Model Plants the Trigger: Answer-Side Backdoor Attacks in Multi-Turn Large Language Models

Safety alignment in Large Language Models LLMs remains vulnerable to backdoor attacks. Existing LLM backdoors are almost all input-centric: activation depends on explicit trigger patterns in the user input, so modern guardrails are built to sanitize the input space. We challenge this assumption...

The Geometry of Harmfulness in Multi-Turn Attacks

Large language models LLMs remain vulnerable to adversarial attacks that circumvent safety alignment to elicit harmful outputs. It remains unclear how harmfulness and refusal representations evolve over the course of multi-turn attacks, and why single-turn defenses are less effective in multi-tur...

AEGIS: Audio Endogenous Guarding Via Internal Signals against Large Audio-Language Model Jailbreaks

Large audio-language models LALMs expand language models to process and interpret audio, but also expose them to heterogeneous audio jailbreaks. We ask whether successful jailbreaks reflect failures to recognize harmful intent or failures occurring after such recognition. Layer-wise probing revea...

SUSE CVE-2026-93710

Dancer2 versions from 2.0.0 before 2.2.0 for Perl dispatch a route that a dying hook refused when the exception handler halts the response in compilehooks. A hook that dies fires core.app.hookexception, then calls cleanup unless the failing hook is the exception handler. A handler that halts does...

CVE-2026-93710

Dancer2 versions from 2.0.0 before 2.2.0 for Perl dispatch a route that a dying hook refused when the exception handler halts the response in compilehooks. A hook that dies fires core.app.hookexception, then calls cleanup unless the failing hook is the exception handler. A handler that halts does...

CVE-2026-93710

Dancer2 versions from 2.0.0 before 2.2.0 for Perl dispatch a route that a dying hook refused when the exception handler halts the response in compilehooks. A hook that dies fires core.app.hookexception, then calls cleanup unless the failing hook is the exception handler. A handler that halts does...

CVE-2026-93710: Improper Cleanup on Thrown Exception

Dancer2 versions from 2.0.0 before 2.2.0 for Perl dispatch a route that a dying hook refused when the exception handler halts the response in compilehooks. A hook that dies fires core.app.hookexception, then calls cleanup unless the failing hook is the exception handler. A handler that halts does...

redteam-skill

Redteam Skill — Multi-Agent Autonomous Penetration Testing Pi...

Same Request, Different Boundary: Evaluating Cybersecurity Assistance across Conversational Contexts

Large Language Models LLMs can solve complex problems, but their misuse in high-risk domains can lead to severe consequences. Model providers therefore restrict assistance for potentially harmful requests. Refusing all cybersecurity requests would therefore harm legitimate users. Providers need a...

The Guard That Cried Wolf: How Scary Words Make Agent Guardrails Refuse Legitimate Actions

Agent guardrails are checks that approve or refuse each action before an LLM executes it. Sometimes they refuse requests that are genuinely safe. This over-safety blocks deployment when a guardrail refuses an authorized task. Evaluating over-safety is hard: at the boundary an authorized action...

AiXamine: Unified Black-Box Evaluation of Cross-Dimensional Trade-Offs in LLM Safety, Security, and Privacy

The critical failure modes in deployed large language models LLMs are cross-dimensional: a model can score 99.3 in safety alignment while refusing one in three benign queries, or improve across every capability metric while losing 21 points in privacy. Existing evaluation frameworks that assess...

OpenAI Launches GPT-5.6-Cyber with Reduced Safeguards for Exploit Development

OpenAI on Monday unveiled a new cybersecurity-focused model called GPT‑5.6‑Cyber that it said is focused on vulnerability research, penetration testing, and incident response. "Built on GPT‑5.6 Sol, it is trained to improve capabilities on several specialized cybersecurity tasks e.g., finding...