batch_jailbreak

Official Repo for Safety in Batches? Understanding and Mitigating Safety Failures in Batch Prompting Kihyun Kim, Hee-Seon Kim, Wonjun Lee, Changick Kim Korea Advanced Institute of Science and Technology KAIST News 2026.09 Our paper has been accepted to AACL-IJCNLP 2026 Main! 🎉 2026.08 Paper is...

CVE-2026-96893 Improper Neutralization of Input Used for LLM Prompting in GitLab

GitLab has remediated an issue in GitLab EE affecting all versions from 19.1 before 19.2.8, 19.3 before 19.3.5, and 19.4 before 19.4.2 that, under certain conditions, could have allowed an authenticated user to inject specially crafted content into AI agent instructions, potentially causing...

CVE-2026-96893 Improper Neutralization of Input Used for LLM Prompting in GitLab

GitLab has remediated an issue in GitLab EE affecting all versions from 19.1 before 19.2.8, 19.3 before 19.3.5, and 19.4 before 19.4.2 that, under certain conditions, could have allowed an authenticated user to inject specially crafted content into AI agent instructions, potentially causing...

CVE-2026-96893

GitLab EE is vulnerable to Improper Neutralization of Input Used for LLM Prompting (CWE-1427) in the GitLab Duo Agent Platform . This flaw allows an authenticated user to inject specially crafted content into AI agent instructions due to improper neutralization of special elements during AI conve...

Autonomous OSS Threat Detection Via Taxonomy-Aligned LLMs

Open source software OSS ecosystems face growing threats from sophisticated supply chain attacks including typosquatting, dependency confusion, Trojan Source obfuscation, malicious build injection, and CI/CD pipeline poisoning. Existing detection approaches rely on signature-based tools and...

Forensic-Aware Continual Adaptation for Image Forgery Localization

The rapid evolution of image manipulation techniques has raised growing public security concerns. Existing Image Forgery Localization IFL methods can accurately localize manipulated regions but are often unable to adapt to newly emerging forgeries. In real-world forensic scenarios, data typically...

redteam-skill

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

EUVD-2026-67846

Improper neutralization of input used for llm prompting in Microsoft Edge for iOS allows an unauthorized attacker to perform spoofing over a network...

Microsoft Edge for iOS Spoofing Vulnerability

Improper neutralization of input used for llm prompting in Microsoft Edge for iOS allows an unauthorized attacker to perform spoofing over a network...

CVE-2026-70331: Undefined Security Weakness

Improper neutralization of input used for llm prompting in Microsoft Edge for iOS allows an unauthorized attacker to perform spoofing over a network...

PT-2026-83265

Name of the Vulnerable Software and Affected Versions Microsoft Edge for iOS affected versions not specified Description Improper neutralization of input used for Large Language Model LLM prompting allows an unauthorized attacker to perform spoofing over a network. LLM prompting refers to the...

Improper Neutralization of Input Used for LLM Prompting

Overview strands-agents-tools is an A collection of specialized tools for Strands Agents Affected versions of this package are vulnerable to Improper Neutralization of Input Used for LLM Prompting via the pythonrepl function in src/strandstools/pythonrepl.py. An attacker can execute arbitrary...

EUVD-2026-65735

Improper neutralization of input used for LLM prompting in the pythonrepl tool in Amazon Strands Agents Tools before 0.8.5 might allow remote actors to execute arbitrary Python code on the agent's host by bypassing the human consent gate, via a crafted prompt that forwards noninteractivemode as a...

CVE-2026-78379 Consent bypass in python_repl tool via batch kwargs forwarding in Amazon Strands Agents Tools

Improper neutralization of input used for LLM prompting in the pythonrepl tool in Amazon Strands Agents Tools before 0.8.5 might allow remote actors to execute arbitrary Python code on the agent's host by bypassing the human consent gate, via a crafted prompt that forwards noninteractivemode as a...

CVE-2026-78379

Amazon Strands Agents Tools (prior to 0.8.5 ) is affected by an improper input neutralization flaw in its python_repl tool. A remote attacker can craft a prompt that forwards the non_interactive_mode keyword argument through the batch tool, thereby bypassing the human consent gate and achieving a...

Benchmarking Identity-Sensitive LLM Outputs for Surveillance and Security Robots

Large language models LLMs are increasingly used to generate textual robot design specifications, interaction policies, and risk assessments during early-stage robot development. Such outputs may influence how surveillance and security robots are conceptualized, documented, and ultimately...

Improper Neutralization of Input Used for LLM Prompting

Overview strands-agents-tools is an A collection of specialized tools for Strands Agents Affected versions of this package are vulnerable to Improper Neutralization of Input Used for LLM Prompting via the shell tool. An attacker can execute arbitrary operating system commands by crafting a prompt...

dynamic-prompting (>=0.2.4, <=0.2.6), embedprepro (>=0.1.0, <=0.12.0) +6 more potentially affected by CVE-2026-9856 via transformers (4.41.1)

transformers PYPI version 4.41.1 is affected by a known vulnerability. The following packages have a transitive dependency on transformers and may be impacted: - dynamic-prompting =0.2.4, =0.1.0, =4.2.4, =0.1.0, =0.0.23, =0.0.4, =0.0.6 Source cves: CVE-2026-9856 Source advisory:...

A Controlled Candidate-Set Benchmark for Offline Satellite-Security Plan Decomposition

Some security-development settings require local models that map an objective to an ordered, checkable plan. We present a low-rank decomposition adapter and release a case-disjoint corpus with 24 authored decompositions and 83 derived next-step examples across 24 satellite-security cases. To...

The Illusion of Secure LLM Code: Closing the Security Gap Via Iterative Reprompting

Large Language Models LLMs are increasingly integrated into software development workflows, yet their ability to autonomously generate secure authentication code remains uncertain. This paper evaluates the security architecture of authentication systems generated by five prominent AI coding...