DNGInspector Structural Analyzer for DNG/TIFF Metadata and IFD Anomaly Detection

This Python script implements a static inspection tool for Digital Negative DNG files by parsing the TIFF-based header and analyzing Image File Directory IFD entries for structural anomalies. The tool validates basic header fields, traverses IFD records, and flags suspicious metadata patterns suc...

Space Fabric: A Satellite-Enhanced Trusted Execution Architecture

The emergence of decentralized satellite networks and orbital computing platforms creates a pressing need for trust architectures that can operate without physical access to the hardware, without reliance on pre-provisioned vendor secrets, and without dependence on a single manufacturer's...

RedEdit: Agentic Red-Teaming of Image Safety Classifiers Via MCTS-Guided Photo-Editing

Image safety classifiers serve as a critical component of contemporary content moderation systems on the internet. However, their resilience against user-style malicious image editing remains underexplored. Such behaviors are highly prevalent in daily scenarios but difficult to fully reproduce. T...

Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems

Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supply-chain risk: malicious contributors can hide harmful behavior inside skills that appear benign under superficial inspection. However, existing...

Token-Level Generalization in LoRA Adapter Backdoors: Attack Characterization and Behavioral Detection

We show that LoRA adapters, the dominant distribution format for fine-tuned LLMs, can be reliably backdoored through training data poisoning while preserving baseline task performance. On a Qwen 2.5 1.5B prompt-injection classifier, a small fraction of poisoned examples drives a...

Towards Cybersecurity SuperIntelligence (CSI): What'S the Best Harness for Cybersecurity?

What is the best harness for cybersecurity AI? Cybersecurity systems are converging on a single execution scaffold per agent, an iterative shell loop driven by a Large Language Model LLM. However, scaffolds are not interchangeable, rarely interoperable, and no single scaffold dominates across all...

CVE-2026-0265 Vulnerability Assessment Tool

CVE-2026-0265 is a remote authentication bypass affecting PAN-OS and Panorama that triggers when an authentication profile uses Cloud Authentication Service CAS. This tool safely detects whether an instance is vulnerable without authenticating any session or modifying any state...

XAI FL-IDS: A Federated Learning and SHAP-Based Explainable Framework for Distributed Intrusion Detection Systems

An Intrusion Detection System IDS is vital in cybersecurity, detecting unauthorized activity across networks. With attacks on network layers increasing, stronger IDSs are needed. Yet most IDSs rely on centralized detection, forcing IoT nodes to ship data to a server, adding overhead and offering ...

Backdooring Masked Diffusion Language Models

Masked diffusion language models MDLMs are emerging as a compelling new paradigm for text generation, but their training-time security remains largely unexplored. Existing backdoor attacks on Gaussian diffusion models or autoregressive language models do not directly apply to MDLMs because MDLMs...

On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies

The security of AI-generated code remains a major obstacle to its widespread adoption. Although code generation models achieve strong performance on functional benchmarks, their outputs frequently contain bugs and security weaknesses that undermine their trustworthiness. Prior work has explored a...

Supply-Chain Poisoning Attacks against LLM Coding Agent Skill Ecosystems

LLM-based coding agents extend their capabilities via third-party agent skills distributed through open marketplaces without mandatory security review. Unlike traditional packages, these skills are executed as operational directives with system-level privileges, so a single malicious skill can...

Street-Legal Physical-World Adversarial Rim for License Plates

Automatic license plate reader ALPR systems are widely deployed to identify and track vehicles. While prior work has demonstrated vulnerabilities in ALPR systems, far less attention has been paid to their legality and physical-world practicality. We investigate whether low-resourced threat actors...

AirPlay RTSP Device Discovery Scanner

The AirPlay RTSP Device Discovery Scanner is a Metasploit auxiliary module designed to safely identify Apple AirPlay-compatible devices by sending a legitimate RTSP OPTIONS request to the default AirPlay service port 7000/TCP. The module performs non-intrusive service fingerprinting only and does...

RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance

Deep neural networks are highly susceptible to backdoor attacks, yet most defense methods to date rely on balanced data, overlooking the pervasive class imbalance in real-world scenarios that can amplify backdoor threats. This paper presents the first in-depth investigation of how the dataset...

Small Language Models for Phishing Website Detection: Cost, Performance, and Privacy Trade-Offs

Phishing websites pose a major cybersecurity threat, exploiting unsuspecting users and causing significant financial and organisational harm. Traditional machine learning approaches for phishing detection often require extensive feature engineering, continuous retraining, and costly infrastructur...

Future-Proofing Cloud Security against Quantum Attacks: Risk, Transition, and Mitigation Strategies

Quantum Computing QC introduces a transformative threat to digital security, with the potential to compromise widely deployed classical cryptographic systems. This survey offers a comprehensive and systematic examination of quantumsafe security for Cloud Computing CC, focusing on the...

Civil Servants As Builders: Enabling Non-IT Staff to Develop Secure Python and R Tools

Current digital government literature focuses on professional in-house IT teams, specialized digital service teams, vendor-developed systems, or proprietary low-code/no-code tools. Almost no scholarship addresses a growing middle ground: technically skilled civil servants outside formal IT roles...

Good News for Script Kiddies? Evaluating Large Language Models for Automated Exploit Generation

Large Language Models LLMs have demonstrated remarkable capabilities in code-related tasks, raising concerns about their potential for automated exploit generation AEG. This paper presents the first systematic study on LLMs' effectiveness in AEG, evaluating both their cooperativeness and technica...

Packet Storm New Exploits for April, 2025

This archive contains all of the 166 exploits added to Packet Storm in April, 2025...

PT-Mark: Invisible Watermarking for Text-To-Image Diffusion Models Via Semantic-Aware Pivotal Tuning

Watermarking for diffusion images has drawn considerable attention due to the widespread use of text-to-image diffusion models and the increasing need for their copyright protection. Recently, advanced watermarking techniques, such as Tree Ring, integrate watermarks by embedding traceable pattern...

Red Hat Security Advisory 2026-55794-03

Red Hat Security Advisory 2026-55794-03 - An update for the 389-ds:1.4 module is now available for Red Hat Enterprise Linux 8.8 Update Services for SAP Solutions and Red Hat Enterprise Linux 8.8 Telecommunications Update Service. Issues addressed include buffer overflow and null pointer...

Poster: Rethinking Security in LLM Code Generation through Real-World Risk Scenarios

Large Language Models LLMs are widely used for code generation, yet their security behavior in realistic development workflows remains underexplored. Existing benchmarks often rely on explicitly specified security requirements, failing to capture real-world scenarios where prompts are frequently...

DARWIN: Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection

Most existing LLM safety evaluation and defense methods follow a static formulation: jailbreak vulnerabilities are evaluated with fixed attack methods, and guardrails are trained on fixed malicious prompt datasets. However, real-world adversaries continuously evolve their capabilities and expand...

Signal-Based Model Access Risk Analysis for AI System Operations Security

Artificial intelligence AI systems are now ubiquitous across domains such as security, finance, healthcare, consumer technology, and large-scale cloud services, where they process massive volumes of data and make consequential decisions daily. This widespread adoption has created a broad attack...

Enhanced Multi-Class DDoS Attack Identification Using a Meta-Learning Ensemble

Distributed Denial of Service DDoS attacks continue to pose significant threats to network availability and security. While many detection systems focus on binary classification attack vs. benign, effective mitigation often requires identifying the specific type of DDoS attack. This paper...

Assessing the Forensic Viability of Android Memory Analysis across Production Builds: A Cross-Version Study of Security Hardening and Structure Preservation

Android memory forensics recovers evidence that never touches disk: decrypted messages, session credentials, and the live internal state of a running application. The tools that perform this recovery depend on debug symbols embedded in libart.so, the Android Runtime library, to locate data...

Joern 4.0.578

Joern is the bug hunter's workbench. With this tool, you can uncover attack surface, sloppy coding practices, and variants of known vulnerabilities using an interactive code analysis shell. Joern supports C, C++, LLVM bitcode, x86 binaries via Ghidra, JVM bytecode via Soot, and Javascript...

Snyk VulnBench JS 1.0: Can LLMs Find the Same Bugs Twice?

We ran 300 repeated vulnerability-finding scans to measure how repeatable agentic large language model LLM security review is on the same JavaScript code, prompt, and benchmark harness. The headline result is that LLM security findings were unevenly repeatable: reference-matched findings were...

An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response

University Academic Management Information Systems ACMIS are high-value targets for a wide spectrum of security threats including brute-force login attacks, payment fraud, privilege escalation, insider data theft, and academic integrity violations. Traditional rule-based intrusion detection syste...

Detecting Aimbot Cheaters in MOGs

Multiplayer Online Games have become a multibillion dollar industry in the entertainment sector. However, the presence of cheaters undermines the experience of honest players and devalues the effort of game developers, as it directly affects player retention, competitive integrity, the legitimacy...

ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree

Agent skills extend AI agents with reusable instructions, tools, scripts, references, and workflows, establishing a security boundary distinct from both model safety and traditional package-malware detection. ClawHub Security Signals is a sanitized dataset of 67,453 latest public OpenClaw skill...

From Prompt Injection to Persistent Control: Defending Agentic Harness against Trojan Backdoors

LLM agents are evolving from conversational chatbots to operational tools in real-world workspaces. In local agentic harnesses, an LLM can read and write files, call tools, and reuse workspace state across sessions. While such capabilities enhance utility, they also expose a new attack surface fo...

OSSEC HIDS 4.1.0

OSSEC is a full platform to monitor and control your systems. It mixes together all the aspects of HIDS host-based intrusion detection, log monitoring and SIM/SIEM together in a simple, powerful and open source solution. This is the source code release...

SEED: Semi-Supervised Continual MalwarE Detection for Tackling ConcEpt Drift on a BuDget

Machine learning based malware detectors become obsolete over time due to concept drift in benign and malware applications. Recent methods rely on fully labeled data and use hierarchical contrastive loss HCL with active learning to improve robustness against drift by exploiting semantic structure...

Validating Threat Modeling Results with the Help of Vulnerable Test Applications

Validating threat modeling results remains difficult because completeness is hard to judge without an external oracle. Existing studies often rely on expert-produced reference models and other human baselines, but these can contain omissions or disagreements. This paper evaluates a complementary,...

No Attack Required: Semantic Fuzzing for Specification Violations in Agent Skills

LLM-powered agents can silently delete documents, leak credentials, or transfer funds on a routine user request, not because the agent was attacked, but because the skill it invoked broke its own declared safety rules. We call these specification violations: benign inputs cause a skill to breach...

Security Risks in Tool-Enabled AI Agents: A Systematic Analysis of Privileged Execution Environments

Tool-enabled AI agents are increasingly deployed in cloud-hosted environments and offered as services, where they perform side-effecting operations through privileged tools within execution environments. While such agents enable powerful automation, the security implications of hosting autonomous...

EDySec: A Deep Learning-Based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem

The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multiphase malware execution, remote access activation, and dynamic payload generation. Traditional Machine Learning ML detectors struggle to detect these...

LLM-Driven Feature-Level Adversarial Attacks on Android Malware Detectors

The rapid growth in both the scale and complexity of Android malware has driven the widespread adoption of machine learning ML techniques for scalable and accurate malware detection. Despite their effectiveness, these models remain vulnerable to adversarial attacks that introduce carefully crafte...

RunawayEvil: Jailbreaking the Image-To-Video Generative Models

Image-to-Video I2V generation synthesizes dynamic visual content from image and text inputs, providing significant creative control. However, the security of such multimodal systems, particularly their vulnerability to jailbreak attacks, remains critically underexplored. To bridge this gap, we...

Beyond Text: Multimodal Jailbreaking of Vision-Language and Audio Models through Perceptually Simple Transformations

Multimodal large language models MLLMs have achieved remarkable progress, yet remain critically vulnerable to adversarial attacks that exploit weaknesses in cross-modal processing. We present a systematic study of multimodal jailbreaks targeting both vision-language and audio-language models,...

Exploiting Web Search Tools of AI Agents for Data Exfiltration

Large language models LLMs are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflows like web searches. The usage of tool-calling and Retrieval Augmented Generation RAG allows LLMs to process and retrieve sensitive corporate data, amplifyi...

WAInjectBench: Benchmarking Prompt Injection Detections for Web Agents

Multiple prompt injection attacks have been proposed against web agents. At the same time, various methods have been developed to detect general prompt injection attacks, but none have been systematically evaluated for web agents. In this work, we bridge this gap by presenting the first...

IPIGuard: a Novel Tool Dependency Graph-Based Defense against Indirect Prompt Injection in LLM Agents

Large language model LLM agents are widely deployed in real-world applications, where they leverage tools to retrieve and manipulate external data for complex tasks. However, when interacting with untrusted data sources e.g., fetching information from public websites, tool responses may contain...

CertDW: Towards Certified Dataset Ownership Verification via Conformal Prediction

Deep neural networks DNNs rely heavily on high-quality open-source datasets e.g., ImageNet for their success, making dataset ownership verification DOV crucial for protecting public dataset copyrights. In this paper, we find existing DOV methods implicitly assume that the verification process is...

Cudy WR3000 Authentication Bypass / Command Injection

Cudy WR3000 routers suffer from authentication bypass vulnerability due to a hard-coded secret and a code injection vulnerability via unsanitized input...

Veeam ONE Reporter 13.1 Remote Code Execution

Veeam ONE Reporter version 13.1 contains an authenticated remote code execution vulnerability in dashboard scheduling. A remote PowerUser can supply an arbitrary command through reportSettings.command, which is subsequently executed without command validation or privilege reduction. Commands...

Cyber-Capable AI Agents: Vulnerabilities, Evaluation Containment, and Defensive Response

Cyber-capable AI agents combine language models with tools, memory, and execution en- vironments to perform multi-step offensive-security tasks. Existing work separately measures cyber capability and catalogs attacks against agent components, but provides less guidance on containing a capable age...

RECEIPT: Deterministic, Reward-Hacking-Resistant Verification for White-Box Agentic XSS Discovery

Cross-Site Scripting XSS remains one of the most prevalent and damaging classes of web vulnerabilities. LLM-based coding agents offer a promising approach to XSS discovery by combining source-code reasoning with interactive testing against a running application. However, a coding agent's claims...

Specter 1.0 NFC Reader / Skimmer Bug-Sweep

Specter turns your Flipper Zero into a pocket counter-surveillance bug-sweep for active 13.56 MHz NFC readers - a hidden card skimmer slipped into a payment terminal, a covert reader behind a door panel, a rogue logger taped under a desk. It passively senses the RF carrier that any powered-on...