ProvAgent: Threat Detection Based on Identity-Behavior Binding and Multi-Agent Collaborative Attack Investigation

Advanced Persistent Threats APTs pose critical challenges to modern cybersecurity due to their multi-stage and stealthy nature. While provenance-based detection approaches show promise in capturing causal attack semantics, current threat provenance practices face two paradoxical issues: 1 expert...

Learning the APT Kill Chain: Temporal Reasoning over Provenance Data for Attack Stage Estimation

Advanced Persistent Threats APTs evolve through multiple stages, each exhibiting distinct temporal and structural behaviors. Accurate stage estimation is critical for enabling adaptive cyber defense. This paper presents StageFinder, a temporal graph learning framework for multi-stage attack...

com.efluid.oss:efluid-datagate-app (>=3.1.3 <=6.1.5), com.efluid.oss:efluid-datagate-app-cucumber (>=3.1.3 <=6.1.5) +5 more potentially affected by CVE-2026-29000 via org.pac4j:pac4j-jwt (>=5.0.1 <=5.7.8)

org.pac4j:pac4j-jwt MAVEN version =5.0.1, =3.1.3, =3.1.3, =0.8.0, =0.8.0, =2.0.6, =2.2.1, =2.0.6, =2.1.0 Source cves: CVE-2026-29000 Source advisory: SNYK:JAVA-ORGPAC4J-15428218...

org.openprovenance.prov:service-templates (>=2.0.6 <=2.1.0), org.webjars.npm:httpntlm (=1.7.7) potentially affected by CVE-2026-27601 via org.webjars.npm:underscore (>=1.12.1 <=1.13.6)

org.webjars.npm:underscore MAVEN version =1.12.1, =2.0.6, =2.1.0 - org.webjars.npm:httpntlm =1.7.7 Source cves: CVE-2026-27601 Source advisory: SNYK:JAVA-ORGWEBJARSNPM-15369787...

Exploiting PendingIntent Provenance Confusion to Spoof Android SDK Authentication

A single authentication bypass in a partner SDK grants attackers the identity of every partner in the ecosystem -- and millions of apps use SDKs with exactly this vulnerability. OWASP's 2024 Mobile Top 10 ranks Inadequate Supply Chain Security as the second most critical mobile risk, explicitly...

Agentic AI As a Cybersecurity Attack Surface: Threats, Exploits, and Defenses in Runtime Supply Chains

Agentic systems built on large language models LLMs extend beyond text generation to autonomously retrieve information and invoke tools. This runtime execution model shifts the attack surface from build-time artifacts to inference-time dependencies, exposing agents to manipulation through untrust...

Unauthorized npm publish of [email protected] with modified postinstall script

Description On February 17, 2026 at 3:26 AM PT, an unauthorized party used a compromised npm publish token to publish an update to Cline CLI on the NPM registry: [email protected]. The published package contains a modified package.json with an added postinstall script: "postinstall": "npm install -g...

GHSA-W5C7-9QQW-6645 OpenClaw inter-session prompts could be treated as direct user instructions

Summary Inter-session messages sent via sessionssend could be interpreted as direct end-user instructions because they were persisted as role: "user" without provenance metadata. Affected Packages / Versions - Package: openclaw npm - Affected versions: = 2026.2.13 Impact A delegated or internal...

OpenClaw inter-session prompts could be treated as direct user instructions

Summary Inter-session messages sent via sessionssend could be interpreted as direct end-user instructions because they were persisted as role: "user" without provenance metadata. Affected Packages / Versions - Package: openclaw npm - Affected versions: = 2026.2.13 Impact A delegated or internal...

Verifiable Provenance of Software Artifacts with Zero-Knowledge Compilation

Verifying that a compiled binary originates from its claimed source code is a fundamental security requirement, called source code provenance. Achieving verifiable source code provenance in practice remains challenging. The most popular technique, called reproducible builds, requires difficult...

Toxic_Flow_Analysis_Framework_For_Agentic_AI

Toxic Flow Analysis TFA Framework A Secure-by-Design framew...

PIDSMaker: Building and Evaluating Provenance-Based Intrusion Detection Systems

Recent provenance-based intrusion detection systems PIDSs have demonstrated strong potential for detecting advanced persistent threats APTs by applying machine learning to system provenance graphs. However, evaluating and comparing PIDSs remains difficult: prior work uses inconsistent preprocessi...

Toward Trustworthy Agentic AI: A Multimodal Framework for Preventing Prompt Injection Attacks

Powerful autonomous systems, which reason, plan, and converse using and between numerous tools and agents, are made possible by Large Language Models LLMs, Vision-Language Models VLMs, and new agentic AI systems, like LangChain and GraphChain. Nevertheless, this agentic environment increases the...

PROVEX: Enhancing SOC Analyst Trust with Explainable Provenance-Based IDS

Modern intrusion detection systems IDS leverage graph neural networks GNNs to detect malicious activity in system provenance data, but their decisions often remain a black box to analysts. This paper presents a comprehensive XAI framework designed to bridge the trust gap in Security Operations...

LeechHijack: Covert Computational Resource Exploitation in Intelligent Agent Systems

Large Language Model LLM-based agents have demonstrated remarkable capabilities in reasoning, planning, and tool usage. The recently proposed Model Context Protocol MCP has emerged as a unifying framework for integrating external tools into agent systems, enabling a thriving open ecosystem of...

Hesperus Is Phosphorus: Mapping Threat Actor Naming Taxonomies at Scale

This paper studies the problem of Threat Actor TA naming convention inconsistency across leading Cyber Threat Intelligence CTI vendors. The current decentralized and proprietary nomenclature creates confusion and significant obstacles for researchers, including difficulties in integrating and...

Securing the Model Context Protocol (MCP): Risks, Controls, and Governance

The Model Context Protocol MCP replaces static, developer-controlled API integrations with more dynamic, user-driven agent systems, which also introduces new security risks. As MCP adoption grows across community servers and major platforms, organizations encounter threats that existing AI...

GraphFaaS: Serverless GNN Inference for Burst-Resilient, Real-Time Intrusion Detection

Provenance-based intrusion detection is an increasingly popular application of graphical machine learning in cybersecurity, where system activities are modeled as provenance graphs to capture causality and correlations among potentially malicious actions. Graph Neural Networks GNNs have...

MAL-2025-147864 Malicious code in sequelize-deimos-cressida-hapi (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 3e70ccd0b2b0e6bba0ae898039b44edfaf5267da39d9d94a84e53158d0f6ba68 This package appears to be part of the tea.xyz token reward campaign that flooded npm. These packages typically contain autopublish scripts auto.js,...

SecTracer: A Framework for Uncovering the Root Causes of Network Intrusions Via Security Provenance

Modern enterprise networks comprise diverse and heterogeneous systems that support a wide range of services, making it challenging for administrators to track and analyze sophisticated attacks such as advanced persistent threats APTs, which often exploit multiple vectors. To address this challeng...