Security of LLM-Generated Code: A Comparative Analysis

The majority of software developers use or are planning to use Artificial Intelligence AI tools in their development processes. Their top reasons include improving productivity and faster learning. In fact, Large Language Model LLM-generated code is currently in production, including in major tec...

PT-2026-42632

Summary lmdeploy hardcodes trust remote code=True in multiple HuggingFace model-loading call sites. The affected code paths are in: text lmdeploy/archs.py lmdeploy/utils.py The vulnerable call sites pass trust remote code=True into HuggingFace Transformers APIs such as AutoConfig.from pretrained,...

Blind Spots in the Guard: How Domain-Camouflaged Injection Attacks Evade Detection in Multi-Agent LLM Systems

Injection detectors deployed to protect LLM agents are calibrated on static, template-based payloads that announce themselves as override directives. We identify a systematic blind spot: when payloads are generated to mimic the domain vocabulary and authority structures of the target document, wh...

Human Vulnerability Assessment in Cybersecurity: A Systematic Literature Review of Methods, Models, and Instruments

In cybersecurity, vulnerability assessment has typically focused on identifying and measuring vulnerabilities within digital assets and technical infrastructures. However, there is growing recognition that this approach alone is inadequate without a structured examination of the human factor, whi...

Prompt Overflow: What the Guardrail Inspects Is Not What the Model Infers

Guardrail models a.k.a. safety checkers are widely deployed to screen user inputs before they reach large language models LLMs, serving as a primary defense against prompt injection attacks. Due to strict context constraints, these models handle overlength prompts through truncation or...

Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications

Large Language Models LLMs have become the predominant paradigm in NLP, advancing both research and industry. As model sizes and pretraining data grow, concerns about Pretraining Data Exposure PDE increase due to the scale and opacity of training datasets. PDE refers to determining whether specif...

BIT-PYTHON-2026-4224 Stack overflow parsing XML with deeply nested DTD content models

When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs...

BIT-PYTHON-MIN-2026-4224 Stack overflow parsing XML with deeply nested DTD content models

When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs...

BIT-LIBPYTHON-2026-4224 Stack overflow parsing XML with deeply nested DTD content models

When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs...

HIDBench: Benchmarking Large Language Models for Host-Based Intrusion Detection

Recent benchmark efforts have advanced the evaluation of large language models LLMs in cybersecurity, including tasks such as penetration testing and vulnerability identification. However, a critical cybersecurity task, namely intrusion detection from system logs, remains unexplored. In this work...

A Large Language Model Approach to Generating Bypass Rules for Malware Evasion in Analysis Sandbox

Sandbox evasion remains a critical challenge for automated malware analysis, as modern malware employs environment checks to detect analysis platforms and suppress malicious behavior. Existing approaches rely on manually crafted bypass rules that require deep reverse engineering of each evasion...

📄 ZTE Unauthenticated Denial of Service

ZTE routers 17+ models suffer from an unauthenticated denial of service vulnerability via an oversized POST body. Title: ZTE Routers 17+ Models - Unauthenticated Denial of Service via Oversized POST Body Date: 2026-05-20 Author: Mina Nageh Salalma Monx Research CVE: CVE-2026-34473 Vendor: ZTE...

cpython: Stack overflow parsing XML with deeply nested DTD content models

A stack overflow flaw has been discovered in the python pyexpat module. When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs. This will result in a program crash...

cpython: Stack overflow parsing XML with deeply nested DTD content models

A stack overflow flaw has been discovered in the python pyexpat module. When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs. This will result in a program crash...

CVE-2026-45365

Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.8.11, an internal-only bypassfilter parameter is exposed on the /openai/chat/completions and /ollama/api/chat HTTP endpoints via FastAPI query string binding, allowing any authenticated...

cpython: Stack overflow parsing XML with deeply nested DTD content models

A stack overflow flaw has been discovered in the python pyexpat module. When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs. This will result in a program crash...

cpython: Stack overflow parsing XML with deeply nested DTD content models

A stack overflow flaw has been discovered in the python pyexpat module. When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs. This will result in a program crash...

CVE-2026-45351

Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.8.9, when a regular user non-admin logs into the application, a http://IP:8080/api/models? web request is initiated by the application and in response, it reveals the system prompt of...

Refusal Evaluation in Coding LLMs and Code Agents: A Systematic Review of Thirteen Malicious-Code Prompt Corpora (2023-2025)

The evaluation of large language model refusal on malicious-coding tasks now spans at least thirteen publicly released prompt corpora AdvBench, the CyberSecEval family, RMCBench, RedCode, MCGMark, JailbreakBench, CySecBench, MalwareBench, CIRCLE, MOCHA, ASTRA, Scam2Prompt / Innoc2Scam-bench, and...

Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-To-Image Diffusion Models

Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are difficult to verify and thus more susceptible to hidden backdoor behaviors. In such ecosystems, a single pretrained model may be sequentially adapt...