Veracode
PulseAugur coverage of Veracode — every cluster mentioning Veracode across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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LLMs introduce new security risks via code generation and component integration
Large language models (LLMs) introduce new security vulnerabilities through both their code generation capabilities and their integration as components within applications. While LLMs can accelerate coding, they often p…
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AI accelerates software prototyping, increasing IT spend and engineer demand · 1 source tracked
Contrary to initial expectations that AI would reduce the need for software engineers, the opposite has occurred, with AI making it cheaper and faster to prototype and justify projects. This phenomenon, akin to Jevons p…
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AI-generated code audit reveals critical security flaws
A pre-launch audit of a deliberately broken AI-generated application revealed significant security vulnerabilities, with 45% of AI-generated code introducing such issues according to a Veracode report. The audit, perfor…
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Vibe coding accelerates development but risks critical step omissions
Vibe coding, a method where developers describe software needs in plain language and let AI agents generate, run, and revise code, is rapidly transforming software development. While this approach accelerates the creati…
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Malware spreads via software updates and AI code generation
The article discusses the increasing threat of malware being delivered through software update automation tools, particularly in the npm registry. While malicious packages are not new, a worm that uses the package regis…
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LLMs Invent Context When Not Provided, Leading to Security Risks
A new analysis highlights a critical issue in how large language models (LLMs) operate: when context is not explicitly provided, models invent it based on their training data, often leading to insecure or incorrect outp…
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AI-driven cyberattacks surge, costing billions and generating vulnerable code
A new IBM report indicates that AI-enabled data breaches have increased by 56% year-over-year, now accounting for one in four malicious breaches and costing an average of $6 billion. This trend is exacerbated by advance…
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AI code assistants generate insecure code, researchers find
AI code assistants like GitHub Copilot often generate code with security vulnerabilities, with studies showing around 40-45% of AI-generated code containing flaws. These models are trained on vast public code corpora, w…
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New dataset trains AI to generate secure code, covering web and AI/ML vulnerabilities
Researchers have introduced SecureCode, a new dataset designed to train AI models to generate more secure code. The dataset addresses both traditional web application security, covering the OWASP Top 10 2021, and AI/ML-…
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Automated Security Testing Tools Crucial for Modern DevSecOps
The article discusses the critical role of automated security testing tools in modern DevSecOps environments. It highlights how the rapid pace of code development and deployment necessitates these tools to identify vuln…
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AI accelerates software entropy, demanding runtime verification
The increasing adoption of AI in software development accelerates entropy, leading to more code and less human oversight. This creates fragility, as security and reliability gaps may not be apparent until runtime. Organ…
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AI coding assistants get real-time policy guardrails
Two articles discuss the implementation and security of Model Context Protocol (MCP) systems, which provide LLMs with real-time organizational context. The first article details an open-source "Architect's Guardrail" de…