CVE-2026-54235

vLLM is an inference and serving engine for large language models LLMs. Prior to 0.23.1rc0, ll temperature validation gates use comparison operators , which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagat...

CVE-2026-47155

vLLM is an inference and serving engine for large language models LLMs. Prior to 0.22.0, vLLM's revision pinning controls do not consistently apply to all artifacts loaded for a model. A deployment that supplies --revision or --code-revision can still load dynamic code, GGUF files, image...

CVE-2026-54233

Affected software: vLLM (inference/serving engine). Vulnerability: decoding an audio file on the /v1/audio/transcriptions endpoint can cause extreme memory growth. A 25 MB OPUS upload decodes to about 14.9 GB of float32 PCM, because the audio decoder concatenates all frames in memory before retur...

EUVD-2026-38332

LangChain is a framework for building agents and LLM-powered applications. Prior to 1.3.9, several LangChain components that resolve filesystem paths or expand search patterns do not consistently confine the resolved path to the intended root directory. Affected behaviors include: a file-search...

CVE-2026-53538 vulnerabilities

Vulnerabilities for packages: airflow-core, litellm, wazuh-manager-fips, airflow-postgres-fips, tritonserver-backend-vllm-cuda-12.9...

CVE-2026-46517

LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, hardcoded "trustremotecode=True" enables HF supply-chain RCE without user opt-in. At time of publication, there are no publicly available patches...

The Emergence of Autonomous Penetration Capabilities in Large Language Model-Powered AI Systems

Nowadays, the autonomous execution of cyberattacks capable of causing substantial real-world harm is widely regarded as one of the critical red lines that frontier AI systems must not cross. Within this broader red-line scenario, autonomous penetration represents a core enabling capability and...

Mind Your Key: An Empirical Study of LLM API Credential Leakage in IOS Apps

The rapid integration of large language models LLMs into mobile applications has introduced a new class of credential security risk: leaked credentials that grant unauthorized access to LLM inference services, causing financial damage to developers. Prior work on credential leakage has focused...

EUVD-2026-35117

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, evaluator create and update mass-assignment allows cross-workspace evaluator takeover. This issue has been patched in version 3.1.2...

EUVD-2026-35116

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, evaluation create and update mass-assignment allows cross-workspace evaluation takeover. This issue has been patched in version 3.1.2...

EUVD-2026-35113

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, CustomTemplate create and update mass-assignment allows cross-workspace template takeover. This issue has been patched in version 3.1.2...

janus-security-platform

Agentic Security Platform Payments-domain SAST + autonomous P...

Steganography without Modification: Hidden Communication Via LLM Seeds

We demonstrate that widely deployed Large Language Model LLM inference stacks harbor a steganographic channel that requires no modification to model weights, sampling code, or output distributions. The channel exploits a structural property of deterministic decoding: pseudo-random number generato...

RadKey: An LLM-Guided RF Backscatter System for Through-Wall Keystroke Inference

In today's digitally connected world, keyboards remain the primary interface for inputting sensitive information, making them a persistent target for eavesdropping attacks. While prior keystroke inference techniques have exploited side-channel signals such as acoustics and vibrations, they...

RECON: An LLM-Enhanced Backward Constraint Analysis Framework

While traditional techniques, such as symbolic execution, provide a principled foundation for precise constraint reasoning in program analysis, they struggle to scale to modern software systems mainly due to path explosion, the need for function modeling, and the loss of semantic intent at...

CVE-2026-31236

A flaw was found in the llm CLI tool. An attacker can exploit a code injection vulnerability by crafting a malicious command with arbitrary Python code in the --functions argument. If a victim is tricked into running this command, it leads to arbitrary code execution on their system, potentially...

CVE-2026-41487

Langfuse is an open source large language model engineering platform. From version 3.68.0 to before version 3.167.0, there is a role-based-access control flaw in the LLM connection update flow. An authenticated, low-privileged user of role “member” in a project could request the update of an...

AI Worm

Researchers have prototyped an AI-powered internet worm. The coolest thing about the prototype is that it carries its own LLM with it, and runs it on computers that have been broken into. This is the closest to John Brunner's original 1975 conception of a computer worm that I've seen...

Beyond Pass/Fail: Using Process Mining to Understand How LLMs Resist (And Fail) Red Team Attacks

Standard AI red teaming evaluations reduce adversarial campaigns to a single binary outcome, attack success rate ASR, not taking into account the sequential structure of how models resist or yield to attacks. We propose applying process mining, a discipline for discovering and analyzing process...

POISE: Position-Aware Undetectable Skill Injection on LLM Agents

Agent skills provide a lightweight mechanism for extending general-purpose agents, but their open format exposes them to skill-poisoning attacks. A practically dangerous injection must stay invisible: if executing the payload derails the user's legitimate task, the resulting failure signal invite...