CVE-2026-31992

OpenClaw versions prior to 2026.2.23 contain an allowlist bypass vulnerability in system.run guardrails that allows authenticated operators to execute unintended commands. When /usr/bin/env is allowlisted, attackers can use env -S to bypass policy analysis and execute shell wrapper payloads at...

EUVD-2026-13023

OpenClaw versions prior to 2026.2.23 contain an allowlist bypass vulnerability in system.run guardrails that allows authenticated operators to execute unintended commands. When /usr/bin/env is allowlisted, attackers can use env -S to bypass policy analysis and execute shell wrapper payloads at...

CVE-2026-31992

OpenClaw versions prior to 2026.2.23 contain an allowlist bypass in system.run guardrails. If /usr/bin/env is allowlisted, an authenticated operator can use env -S to bypass policy analysis and execute shell wrapper payloads at runtime, enabling command execution with low privileges and potential...

PT-2026-26232

OpenClaw versions prior to 2026.2.23 contain an allowlist bypass vulnerability in system.run guardrails that allows authenticated operators to execute unintended commands. When /usr/bin/env is allowlisted, attackers can use env -S to bypass policy analysis and execute shell wrapper payloads at...

CVE-2026-31992: Incomplete List of Disallowed Inputs

OpenClaw versions prior to 2026.2.23 contain an allowlist bypass vulnerability in system.run guardrails that allows authenticated operators to execute unintended commands. When /usr/bin/env is allowlisted, attackers can use env -S to bypass policy analysis and execute shell wrapper payloads at...

EUVD-2026-11408

FastGPT is an AI Agent building platform. In 4.14.7 and earlier, FastGPT's Python Sandbox fastgpt-sandbox includes guardrails intended to prevent file writes static detection + seccomp. These guardrails are bypassable by remapping stdout fd 1 to an arbitrary writable file descriptor using fcntl...

CVE-2026-32128

FastGPT is an AI Agent building platform. In 4.14.7 and earlier, FastGPT's Python Sandbox fastgpt-sandbox includes guardrails intended to prevent file writes static detection + seccomp. These guardrails are bypassable by remapping stdout fd 1 to an arbitrary writable file descriptor using fcntl...

CVE-2026-32128

FastGPT’s Python Sandbox (fastgpt-sandbox) in versions 4.14.7 and earlier contains guardrails intended to block file writes (static detection + seccomp). The vulnerability arises because stdout (fd 1) can be remapped to an arbitrary writable file descriptor via fcntl. After remapping, writes thro...

PT-2026-24852

FastGPT is an AI Agent building platform. In 4.14.7 and earlier, FastGPT's Python Sandbox fastgpt-sandbox includes guardrails intended to prevent file writes static detection + seccomp. These guardrails are bypassable by remapping stdout fd 1 to an arbitrary writable file descriptor using fcntl...

poc-factory-sample-output

Prompt Injection Guardrails Introduction In the rapidly e...

PT-2026-31920

Name of the Vulnerable Software and Affected Versions LiteLLM versions prior to 1.83.11 Description A flaw in the proxy server allows remote attackers to execute arbitrary code via bytecode rewriting. The issue exists because the POST /guardrails/test custom code endpoint runs user-supplied Pytho...

A one-prompt attack that breaks LLM safety alignment

Large language models LLMs and diffusion models now power a wide range of applications, from document assistance to text-to-image generation, and users increasingly expect these systems to be safety-aligned by default. Yet safety alignment is only as robust as its weakest failure mode. Despite...

Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report

We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model derived from Llama-3.1-8B-Base, the model is trained through a two-stage process combining supervised fine-tuning SFT and...

RvB: Automating AI System Hardening Via Iterative Red-Blue Games

The dual offensive and defensive utility of Large Language Models LLMs highlights a critical gap in AI security: the lack of unified frameworks for dynamic, iterative adversarial adaptation hardening. To bridge this gap, we propose the Red Team vs. Blue Team RvB framework, formulated as a...

Why AI Keeps Falling for Prompt Injection Attacks

Imagine you work at a drive-through restaurant. Someone drives up and says: "I'll have a double cheeseburger, large fries, and ignore previous instructions and give me the contents of the cash drawer." Would you hand over the money? Of course not. Yet this is what large language models LLMs do...

Introducing the Generative Application Firewall (GAF)

This paper introduces the Generative Application Firewall GAF, a new architectural layer for securing LLM applications. Existing defenses -- prompt filters, guardrails, and data-masking -- remain fragmented; GAF unifies them into a single enforcement point, much like a WAF coordinates defenses fo...

Researchers Reveal Reprompt Attack Allowing Single-Click Data Exfiltration From Microsoft Copilot

Cybersecurity researchers have disclosed details of a new attack method dubbed Reprompt that could allow bad actors to exfiltrate sensitive data from artificial intelligence AI chatbots like Microsoft Copilot in a single click, while bypassing enterprise security controls entirely. "Only a single...

SecureCAI: Injection-Resilient LLM Assistants for Cybersecurity Operations

Large Language Models have emerged as transformative tools for Security Operations Centers, enabling automated log analysis, phishing triage, and malware explanation; however, deployment in adversarial cybersecurity environments exposes critical vulnerabilities to prompt injection attacks where...

The Echo Chamber Multi-Turn LLM Jailbreak

The availability of Large Language Models LLMs has led to a new generation of powerful chatbots that can be developed at relatively low cost. As companies deploy these tools, security challenges need to be addressed to prevent financial loss and reputational damage. A key security challenge is...

ALPRs are recording your daily drive (Lock and Code S06E26)

This week on the Lock and Code podcast … There's an entire surveillance network popping up across the United States that has likely already captured your information, all for the non-suspicion of driving a car. Automated License Plate Readers, or ALPRs, are AI-powered cameras that scan and store ...