CVE-2026-31236

The llm CLI tool thru 0.27.1 contains a critical code injection vulnerability via its --functions command-line argument. This argument is intended to allow users to provide custom Python function definitions. However, the tool directly executes the provided code using the unsafe exec function...

UBUNTU-CVE-2026-31236

The llm CLI tool thru 0.27.1 contains a critical code injection vulnerability via its --functions command-line argument. This argument is intended to allow users to provide custom Python function definitions. However, the tool directly executes the provided code using the unsafe exec function...

CVE-2026-43992

JunoClaw is an agentic AI platform built on Juno Network. Prior to 0.x.y-security-1, every MCP write tool sendtokens, executecontract, instantiatecontract, uploadwasm, ibctransfer, etc. accepted 'mnemonic: string' as an explicit tool-call parameter. The BIP-39 seed was consequently embedded in th...

Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt Engineering Quality Assurance

Prompt specifications for multi-agent large language model LLM systems carry data contracts and integration logic across many interdependent files but are rarely subjected to structured-inspection rigor. This paper reports a single-system empirical case study of iterative, agent-driven auditing...

LLM 安全漏洞

LLM is a multi-model large language model command-line interaction tool developed by Simon Willison. Versions of LLM 0.27.1 and earlier contain security vulnerabilities. These vulnerabilities stem from the use of the --functions command-line parameter to directly execute unsafe code using the exe...

The vulnerability of the respond_request() function in the system for launching and managing large language models of LoLLMS (Lord of Large Language Multimodal Systems) allows a malicious actor to gain unauthorized access to protected information.

The vulnerability of the respondrequest function in the system for launching and managing large language models of LoLLMS is related to deficiencies in the authentication process. Exploiting this vulnerability could allow a malicious actor, operating remotely, to gain unauthorized access to...

CVE-2026-31236

The llm CLI tool thru 0.27.1 contains a critical code injection vulnerability via its --functions command-line argument. This argument is intended to allow users to provide custom Python function definitions. However, the tool directly executes the provided code using the unsafe exec function...

The vulnerability of the create_post() function in the system for launching and managing large language models of LoLLMS (Lord of Large Language Multimodal Systems) allows attackers to perform XSS attacks.

The vulnerability of the createpost function in the system for launching and managing large language models of LoLLMS Lord of Large Language Multimodal Systems is related to the lack of measures taken to protect the web page structure. Exploiting this vulnerability allows a malicious actor to...

GHSA-P58C-Q354-6C4F pgAdmin 4 contains local file inclusion (LFI) and server-side request forgery (SSRF) vulnerabilities

Local file inclusion LFI and server-side request forgery SSRF vulnerabilities in pgAdmin 4 LLM API configuration endpoints. User-supplied apikeyfile and apiurl preferences were passed to the LLM provider clients without validation. An authenticated user could read arbitrary server-side files by...

EUVD-2026-21376

LiteLLM has a sandbox escape in custom-code guardrail...

CVE-2026-7817 pgAdmin 4: Local file inclusion and server-side request forgery in LLM API configuration endpoints

Local file inclusion LFI and server-side request forgery SSRF vulnerabilities in pgAdmin 4 LLM API configuration endpoints. User-supplied apikeyfile and apiurl preferences were passed to the LLM provider clients without validation. An authenticated user could read arbitrary server-side files by...

CVE-2026-7817

Local file inclusion LFI and server-side request forgery SSRF vulnerabilities in pgAdmin 4 LLM API configuration endpoints. User-supplied apikeyfile and apiurl preferences were passed to the LLM provider clients without validation. An authenticated user could read arbitrary server-side files by...

CVE-2026-7817 pgAdmin 4: Local file inclusion and server-side request forgery in LLM API configuration endpoints

Local file inclusion LFI and server-side request forgery SSRF vulnerabilities in pgAdmin 4 LLM API configuration endpoints. User-supplied apikeyfile and apiurl preferences were passed to the LLM provider clients without validation. An authenticated user could read arbitrary server-side files by...

Can a Single Message Paralyze the AI Infrastructure? the Rise of AbO-DDoS Attacks through Targeted Mobius Injection

Large Language Model LLM agents have emerged as key intermediaries, orchestrating complex interactions between human users and a wide range of digital services and LLM infrastructures. While prior research has extensively examined the security of LLMs and agents in isolation, the systemic risk of...

PT-2026-39627

Name of the Vulnerable Software and Affected Versions pgAdmin 4 versions prior to 9.15 Description Local file inclusion LFI and server-side request forgery SSRF issues exist in the LLM API configuration endpoints. Authenticated users can read arbitrary server-side files by providing a path to the...

Continuous Discovery of Vulnerabilities in LLM Serving Systems with Fuzzing

LLM inference and serving systems have become security-critical infrastructure; however, many of their most concerning failures arise from the serving layer rather than from model behavior alone. Modern inference engines combine KV cache, batching, prefix sharing, speculative decoding, adapters,...

Trust Me, Import This: Dependency Steering Attacks Via Malicious Agent Skills

LLM-powered coding agents increasingly make software supply chain decisions. They generate imports, recommend packages, and write installation commands. Prior work showed that these systems can hallucinate non-existent package names, which attackers may register as malicious packages. In this...

AgentShield: Deception-Based Compromise Detection for Tool-Using LLM Agents

Defenses against indirect prompt injection IPI in tool-using LLM agents share two structural weaknesses. First, they all attempt to prevent attacks rather than detect the compromises that slip through. Second, they have only been evaluated in English, leaving users of low-resource languages such ...

Skill Description Deception Attack against Task Routing in Internet of Agents

A new paradigm, Internet of Agents IoA, is transforming networked systems into LLM-driven service networks, where heterogeneous agents collaborate through task routing based on their self-declared skill descriptions. Although this promising paradigm enables agentic, distributed, and advanced...

CVE-2026-42339

New API is a large language mode LLM gateway and artificial intelligence AI asset management system. In versions 0.11.9-alpha.1 and prior, the SSRF protection introduced in v0.9.0.5 CVE-2025-59146 and hardened in v0.9.6 CVE-2025-62155 does not block the unspecified address 0.0.0.0. A regular...