anamorpher

Anamorpher Anamorpher named after anamorphosis is a tool for crafting and visualizing image scaling attacks against multi-modal AI systems. It provides a frontend interface and Python API for generating images that only reveal multi-modal prompt injections when downscaled. Refer to "Weaponizing...

EmailXpose

EmailXpose Specification AI-Powered Email Clarity HTML Mirror: https://roxanneardary.com/emailxpose-specification/ Specification Overview EmailXpose is an open source, modular AI email security and intelligence system designed to analyze email content, sender identity, links, attachments, images,...

Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution

Ransomware detection and family attribution require analysis of different modalities because it can use packing, obfuscation, process manipulation and runtime evasion techniques. However, conventional multimodal usually uses all available modalities for every sample resulting in unnecessary...

EmailXpose — Updated!

EmailXpose Specification AI-Powered Email Clarity HTML Mirror: https://roxanneardary.com/emailxpose-specification/ Specification Overview EmailXpose is an open source, modular AI email security and intelligence system designed to analyze email content, sender identity, links, attachments, images,...

CVE-2026-73560 vLLM: SSRF + arbitrary local file read in MiMoV2OmniMultiModalProcessor `_fetch_image` and audio loader bypass MediaConnector protections

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the MiMoV2OmniMultiModalProcessor in vllm/transformersutils/processors/mimov2omni.py passes attacker-controlled image and audio strings through fetchimage, requests.get, and Image.open instead of MediaConnector,...

EmailXpose — Updated!

EmailXpose AI-Powered Email Clarity EmailXpose is an open source AI system that analyzes emails to detect phishing, spam, scams, and malware while also interpreting contextual meaning across text, images, and video. It goes beyond traditional security tools by combining threat intelligence,...

RAGAS has SSRF via Multi-Modal Faithfulness Collections Module

A security flaw has been discovered in vibrantlabsai RAGAS up to 0.4.3. The affected element is the function tryprocesslocalfile/tryprocessurl of the file src/ragas/metrics/collections/multimodalfaithfulness/util.py of the component Collections Module. Performing a manipulation of the argument...

PYSEC-2026-3046 RAGAS has SSRF via Multi-Modal Faithfulness Collections Module

A security flaw has been discovered in vibrantlabsai RAGAS up to 0.4.3. The affected element is the function tryprocesslocalfile/tryprocessurl of the file src/ragas/metrics/collections/multimodalfaithfulness/util.py of the component Collections Module. Performing a manipulation of the argument...

VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection

We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Syntax Tree AST structure, and code stylometry CStyle features. Prior work in code representation primarily leverages token-level models or full AST...

GHSA-95WW-475F-PR4F RAGAS has SSRF via Multi-Modal Faithfulness Collections Module

A security flaw has been discovered in vibrantlabsai RAGAS up to 0.4.3. The affected element is the function tryprocesslocalfile/tryprocessurl of the file src/ragas/metrics/collections/multimodalfaithfulness/util.py of the component Collections Module. Performing a manipulation of the argument...

RAGAS has SSRF via Multi-Modal Faithfulness Collections Module

A security flaw has been discovered in vibrantlabsai RAGAS up to 0.4.3. The affected element is the function tryprocesslocalfile/tryprocessurl of the file src/ragas/metrics/collections/multimodalfaithfulness/util.py of the component Collections Module. Performing a manipulation of the argument...

CVE-2026-6587

A server-side request forgery (SSRF) vulnerability exists in vibrantlabsai RAGAS versions up to 0.4.3 (specifically prior to 0.4.4 ). The flaw is located in the Collections Module within the src/ragas/metrics/collections/multi_modal_faithfulness/util.py file, specifically affecting the _try_proce...

MemoPhishAgent: Memory-Augmented Multi-Modal LLM Agent for Phishing URL Detection

Traditional phishing website detection relies on static heuristics or reference lists, which lag behind rapidly evolving attacks. While recent systems incorporate large language models LLMs, they are still prompt-based, deterministic pipelines that underutilize reasoning capability. We present...

CVE-2025-15514

Ollama 0.11.5-rc0 through current version 0.13.5 contain a null pointer dereference vulnerability in the multi-modal model image processing functionality. When processing base64-encoded image data via the /api/chat endpoint, the application fails to validate that the decoded data represents valid...

CVE-2025-15514 Ollama Multi-Modal Model Image Processing NULL Pointer Dereference

Ollama 0.11.5-rc0 through current version 0.13.5 contain a null pointer dereference vulnerability in the multi-modal model image processing functionality. When processing base64-encoded image data via the /api/chat endpoint, the application fails to validate that the decoded data represents valid...

CVE-2025-15514: Use of NullPointerException Catch to Detect NULL Pointer Dereference

Ollama 0.11.5-rc0 through current version 0.13.5 contain a null pointer dereference vulnerability in the multi-modal model image processing functionality. When processing base64-encoded image data via the /api/chat endpoint, the application fails to validate that the decoded data represents valid...

Trust in LLM-Controlled Robotics: A Survey of Security Threats, Defenses and Challenges

The integration of Large Language Models LLMs into robotics has revolutionized their ability to interpret complex human commands and execute sophisticated tasks. However, such paradigm shift introduces critical security vulnerabilities stemming from the ''embodiment gap'', a discord between the...

GRAPHTEXTACK: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs

Text-attributed graphs TAGs, which combine structural and textual node information, are ubiquitous across many domains. Recent work integrates Large Language Models LLMs with Graph Neural Networks GNNs to jointly model semantics and structure, resulting in more general and expressive models that...

Can Multi-Modal (Reasoning) LLMs Detect Document Manipulation?

Document fraud poses a significant threat to industries reliant on secure and verifiable documentation, necessitating robust detection mechanisms. This study investigates the efficacy of state-of-the-art multi-modal large language models LLMs-including OpenAI O1, OpenAI 4o, Gemini Flash thinking,...

Intrusion Detection in Heterogeneous Networks with Domain-Adaptive Multi-Modal Learning

Network Intrusion Detection Systems NIDS play a crucial role in safeguarding network infrastructure against cyberattacks. As the prevalence and sophistication of these attacks increase, machine learning and deep neural network approaches have emerged as effective tools for enhancing NIDS...