89 matches found
ChainFuzzer: Greybox Fuzzing for Workflow-Level Multi-Tool Vulnerabilities in LLM Agents
Tool-augmented LLM agents increasingly rely on multi-step, multi-tool workflows to complete real tasks. This design expands the attack surface, because data produced by one tool can be persisted and later reused as input to another tool, enabling exploitable source-to-sink dataflows that only...
Systematic Scaling Analysis of Jailbreak Attacks in Large Language Models
Large language models remain vulnerable to jailbreak attacks, yet we still lack a systematic understanding of how jailbreak success scales with attacker effort across methods, model families, and harm types. We initiate a scaling-law framework for jailbreaks by treating each attack as a...
On Moltbook
The MIT Technology Review has a good article on Moltbook, the supposed AI-only social network: Many people have pointed out that a lot of the viral comments were in fact posted by people posing as bots. But even the bot-written posts are ultimately the result of people pulling the strings, more...
Improper Neutralization of Input Used for LLM Prompting
Overview @n8n/n8n-nodes-langchain is a Affected versions of this package are vulnerable to Improper Neutralization of Input Used for LLM Prompting via the Guardrail node. An attacker can modify workflow input to circumvent intended restrictions by crafting specific input values. Workaround This...
Understanding Human-AI Collaboration in Cybersecurity Competitions
Capture-the-Flag CTF competitions are increasingly becoming a testbed for evaluating AI capabilities at solving security tasks, due to the controlled environments and objective success criteria. Existing evaluations have focused on how successful AI is at solving CTF challenges in isolation from...
Mind the Gap: Evaluating LLMs for High-Level Malicious Package Detection Vs. Fine-Grained Indicator Identification
The prevalence of malicious packages in open-source repositories, such as PyPI, poses a critical threat to the software supply chain. While Large Language Models LLMs have emerged as a promising tool for automated security tasks, their effectiveness in detecting malicious packages and indicators...
Benchmarking Large Language Models for Zero-Shot and Few-Shot Phishing URL Detection
The Uniform Resource Locator URL, introduced in a connectivity-first era to define access and locate resources, remains historically limited, lacking future-proof mechanisms for security, trust, or resilience against fraud and abuse, despite the introduction of reactive protections like HTTPS...
Rethinking On-Device LLM Reasoning: Why Analogical Mapping Outperforms Abstract Thinking for IoT DDoS Detection
The rapid expansion of IoT deployments has intensified cybersecurity threats, notably Distributed Denial of Service DDoS attacks, characterized by increasingly sophisticated patterns. Leveraging Generative AI through On-Device Large Language Models ODLLMs provides a viable solution for real-time...
LLMs in Code Vulnerability Analysis: A Proof of Concept
Context: Traditional software security analysis methods struggle to keep pace with the scale and complexity of modern codebases, requiring intelligent automation to detect, assess, and remediate vulnerabilities more efficiently and accurately. Objective: This paper explores the incorporation of...
CVE-2021-22449
There is a logic vulnerability in Elf-G10HN 1.0.0.608. An unauthenticated attacker could perform specific operations to exploit this vulnerability. Due to insufficient security design, successful exploit could allow an attacker to add users to be friends without prompting in the target device...
Chasing Shadows: Pitfalls in LLM Security Research
Large language models LLMs are increasingly prevalent in security research. Their unique characteristics, however, introduce challenges that undermine established paradigms of reproducibility, rigor, and evaluation. Prior work has identified common pitfalls in traditional machine learning researc...
Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection
Few-shot prompting has emerged as a practical alternative to fine-tuning for leveraging the capabilities of large language models LLMs in specialized tasks. However, its effectiveness depends heavily on the selection and quality of in-context examples, particularly in complex domains. In this wor...
ReVul-CoT: Towards Effective Software Vulnerability Assessment with Retrieval-Augmented Generation and Chain-Of-Thought Prompting
Context: Software Vulnerability Assessment SVA plays a vital role in evaluating and ranking vulnerabilities in software systems to ensure their security and reliability. Objective: Although Large Language Models LLMs have recently shown remarkable potential in SVA, they still face two major...
From LLMs to Agents: A Comparative Evaluation of LLMs and LLM-Based Agents in Security Patch Detection
The widespread adoption of open-source software OSS has accelerated software innovation but also increased security risks due to the rapid propagation of vulnerabilities and silent patch releases. In recent years, large language models LLMs and LLM-based agents have demonstrated remarkable...
CVE-2025-64320
Improper Neutralization of Input Used for LLM Prompting vulnerability in Salesforce Agentforce Vibes Extension allows Code Injection.This issue affects Agentforce Vibes Extension: before 3.2.0...
CVE-2025-64321
Improper Neutralization of Input Used for LLM Prompting vulnerability in Salesforce Agentforce Vibes Extension allows Manipulating Writeable Configuration Files.This issue affects Agentforce Vibes Extension: before 3.3.0...
CVE-2025-64318
Improper Neutralization of Input Used for LLM Prompting vulnerability in Salesforce Mulesoft Anypoint Code Builder allows Manipulating Writeable Configuration Files.This issue affects Mulesoft Anypoint Code Builder: before 1.12.1...
CVE-2025-64318
Improper Neutralization of Input Used for LLM Prompting vulnerability in Salesforce Mulesoft Anypoint Code Builder allows Manipulating Writeable Configuration Files.This issue affects Mulesoft Anypoint Code Builder: before 1.12.1...
CVE-2025-64321
Improper Neutralization of Input Used for LLM Prompting vulnerability in Salesforce Agentforce Vibes Extension allows Manipulating Writeable Configuration Files.This issue affects Agentforce Vibes Extension: before 3.3.0...