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.
Safeguard is growing from a posture and findings platform into a first-party detection and prevention platform — first-party AppSec, defensive red-teaming, AI security, data security, runtime/CNAPP, and a supply-chain package firewall — all feeding one prioritized findings model.
Clear answers on securing agentic AI — what makes autonomy risky, how tool scope and identity work, prompt injection and confused-deputy failures, and how Safeguard governs agents that act on your systems.
How an AI can be trusted to fix security vulnerabilities — the role of reachability, validation, and human review in keeping AI-authored remediation accurate and safe.
Your AI supply chain is not just your npm dependencies anymore. It is the models you download, the weights you load, and the datasets you train on — and each is an attack surface most software security programs have never inventoried.
A balanced 2026 comparison of the leading open-source license compliance tools — FOSSA, Black Duck, Mend, Snyk, and the ScanCode/FOSSology open-source stack — with an honest look at where Safeguard fits.
bundler-audit checks your Gemfile.lock against the ruby-advisory-db and flags insecure gem sources. Here is how to run it in Ruby and Rails projects — and beyond.
CVE-2023-4966, Citrix Bleed, let unauthenticated attackers read memory from NetScaler appliances and steal valid session tokens — hijacking sessions and bypassing multi-factor authentication.
How the multi-tenant and dedicated-VPC cloud deployments work: tenant isolation, data handling, key ownership, latency, and when cloud is the right choice versus self-hosting.
A vendor-neutral 2026 FAQ on comparing software supply chain security platforms — the dimensions that matter, how the major players differ, and how to run a fair bake-off.
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