CVE-2026-55534 PraisonAI serve agents --api-key is ignored, allowing unauthenticated remote agent execution

PraisonAI is a multi-agent teams system. From praisonai 4.6.34 until 4.6.58, praisonai serve agents accepts --api-key but createagentsapp does not authenticate POST /agents or POST /agents/agentname. A network caller can invoke configured agents without credentials even when an API key was...

Towards Automated Cyber Threat Intelligence Elicitation in Underground Forums

Cyber threat intelligence from underground forums has traditionally relied on passive monitoring. However, as users have become more aware of large-scale data collection, valuable intelligence has become increasingly rare in open forums, often migrating instead to private or harder-to-reach space...

Directory Traversal

Overview agno is an Agno: a lightweight library for building Multi-Agent Systems Affected versions of this package are vulnerable to Directory Traversal through the readfile, savetofile, and runpythonfile actions. An attacker can read, write, or execute arbitrary files by supplying a filename wit...

Autonomous Cyber Defense in Connected Vehicles: A Multi-Agent Approach to V2X Security

A connected vehicle has roughly 100 milliseconds to decide whether an incoming Basic Safety Message is real or fabricated. If a false emergency braking alert reaches the planning pipeline in time, the car brakes - a safety failure triggered by a security failure. Existing intrusion detection...

Security of Foundation-Model-Powered Embodied Agents: Attack Surfaces, Attacks, Defenses, and Evaluation

Foundation models are increasingly used for perception, reasoning, planning, and action generation in embodied agents, creating security risks that can propagate from digital inputs to physical behavior. Existing surveys often organize threats by mechanisms such as jailbreaks, prompt injection,...

strix v1.5.1

Strix The open-source AI pentesting tool. Autonomous AI hackers that find and fix your app’s vulnerabilities. !TIP New! Strix integrates seamlessly with GitHub Actions and CI/CD pipelines. Automatically scan for vulnerabilities on every pull request and block insecure code before it reaches...

Defending Retrieval-Augmented Intrusion Detection against Knowledge Poisoning and Prompt Injection

Retrieval-Augmented Generation RAG enables large language models to classify network flows and generate human-readable incident reports by retrieving semantically similar historical traffic from a vector knowledge base. However, the retrieval layer introduces vulnerabilities to knowledge poisonin...

langgraph-agentic-research-api-poc

LANGGRAPH-AGENTIC-RESEARCH-API-POC - High-Impact Autonomous Ag...

PromptShield Home: Ambient Multimodal Prompt Injection Defense for Smart-Home Agents

Smart-home assistants increasingly use multimodal large language models MLLMs that perceive video and audio directly. This raises a safety question specific to the home: can the agent tell a genuine user command from ambient or externally-sourced content, television speech, on-screen text, or an...

CLEAR: Causal Context-Based Agentic Reasoning for Vulnerability Detection

Detecting source code vulnerabilities is increasingly difficult as modern security flaws are rooted in complex causal dependencies between execution flows, control conditions, and program states. Despite recent advances in Large Language Models LLMs and multi-agent frameworks, existing approaches...

When Prompts Control Robots: Prompt Injection Attacks in Multi-Agent Robotic Systems

Large language models are increasingly integrated into autonomous robotic systems for task planning and control, but this integration exposes them to prompt injection attacks that can lead to unsafe decisions and physical harm. Multi-agent settings increase the risks through cross-agent...

Adversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Structural Vulnerabilities in Agentic AI Architectures

Multi-agent LLM pipelines orchestrate multiple specialized language model agents into structured workflows where intermediate outputs are passed across agents to solve complex tasks. This design introduces a security gap absent in single-agent settings: once an agent accepts adversarial content, ...

Agent Harness Distillation: Inference-Time Harness Extraction and Exploitation in Autonomous Multi-Agent Systems

Autonomous multi-agent systems AMAS built on large language models LLMs, such as Hermes, increasingly rely on inference-time harnesses to coordinate reasoning and action. Constructing these harnesses requires substantial engineering effort and computational resources, as they are iteratively...

ThreatForest: Multi-Agent Attack Tree Generation with Pluggable TTP Framework Mapping

Threat modeling is essential for secure software development, yet manual analysis of cloud-native architectures is slow and demands scarce security expertise. We present ThreatForest, a multi-agent system that generates structured attack trees from source code repositories, maps attack steps to...

(EC)2: Event-Centric Explainability for Cybersecurity through Multi-Agent LLM Investigations

Security operations centers rely on anomaly detection systems to flag suspicious events. Feature-level explanations for anomaly detectors offer limited value for operational investigations. To effectively handle alerts, analysts need to know contextual relationships and need actionable...

Early Detection of Distributed Backdoors in Multi-Agent LLM Systems: A Characterization Study

Multi-agent LLM systems can be attacked by a payload that no single agent ever holds in full: a poisoned tool hides encrypted fragments in its observations, spreads them across several agents, and an external step reassembles and executes them after the run. Per-step safety checks that judge each...

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis

Malware analysis demands rapid interpretation of complex detonation reports spanning filesystem, network, and process behaviours. While large language models LLMs demonstrate impressive capabilities for technical artifact interpretation, the opacity and escalating API costs of closed-weight...

CVE-2026-47394 PraisonAI vulnerable to unauthenticated arbitrary file read via MCP workflow.show, workflow.validate, deploy.validate

PraisonAI is a multi-agent teams system. Prior to version 4.6.40, the fix for GHSA-9mqq-jqxf-grvw / CVE-2026-44336 is incomplete. The original advisory description named four vulnerable handlers in mcpserver/adapters/clitools.py. Commit 68cc9427 "fixsecurity: harden MCP rules path handling…" adde...

CVE-2026-47416: Improper Privilege Management

PraisonAI Platform is the platform layer for the PraisonAI multi-agent teams system. Versions prior to 0.1.4 are vulnerable to vertical privilege escalation. The PATCH /workspaces/workspaceid/members/userid endpoint is gated by requireworkspacememberworkspaceid, which defaults to minrole="member"...

Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning

Recent LLM-based systems have shown promising capabilities for security-focused code analysis. Malware understanding, however, poses a distinct challenge: analysts must reconstruct high-level malicious behaviors under partial observability from sparse, dispersed evidence intertwined with benign...