Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
A concrete look at how AI safety benchmark evaluation, LLM safety scorecards, and capability testing actually measure model risk in 2026 — and where they fall short.
A practical look at how SSDLC practices evolved in 2025, what worked, what failed, and why most organizations are still getting the basics wrong.
CWE-338 explained through the Debian OpenSSL and Android Bitcoin SecureRandom breaches — how weak PRNGs get exploited, and how to detect and fix them.
A practical buyer's guide to evaluating an automated red teaming platform for continuous AI testing, with a fair roundup of six real vendors and tools.
Weak cryptography vulnerabilities like MD5, ECB mode, and undersized RSA keys quietly break real systems. Learn how, with cases from Adobe, Logjam, and SHAttered.
Prompt injection attacks trick AI models into obeying attacker instructions hidden in data or user input, and there's still no complete fix.
Certificate validation bypass flaws silently disable TLS's identity guarantees, opening the door to man-in-the-middle attacks. Here's how they happen and how to catch them.
How attackers hide malicious instructions inside webpages, documents, and retrieved content to hijack AI systems — and why RAG pipelines are especially exposed.
Small inputs, big CPU spikes: how algorithmic complexity DoS vulnerabilities like ReDoS and hash flooding crash apps with a single request.
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