Secret Scanning Has Fewer False Alerts. Evidence Still Matters
GitHub improved secret detectors on November 5. Learn how source context, credential status and ownership support a safer response.
25 articles
GitHub improved secret detectors on November 5. Learn how source context, credential status and ownership support a safer response.
Dependabot can propose version updates for agent dependencies. The change puts skills and instructions into an existing review workflow.
A GitHub Actions policy change puts privileged pull request workflows under scrutiny. Here is what maintainers can do before enforcement.
An internal DeepSeek evaluation separates exploit capability from operational restraint. Define scope, evidence and cleanup before autonomous testing.
Separate PHP runtime exposure from application findings, verify worker replacement and keep remediation evidence reviewable with Plexicus.
EMBRACE is a useful reminder that an embedded browser does not automatically keep the security boundaries of a standalone browser.
Turn AI security benchmark claims into a scoped evaluation with reproducible findings, reviewed patches and deployment retests.
A source review of three high-severity n8n alerts shows why scan provenance and credential context matter before declaring a leak.
Review browser-loaded scripts, test integrity controls and retain deployment evidence after the Convertr analytics-script incident.
Map embedded Wasmtime dependencies to shipped artifacts, choose the correct advisory fix and verify rebuilt deployments with a Plexicus evidence workflow.
A practical evidence workflow for testing authorization boundaries, connecting code context to impact, and reviewing remediation with Plexicus.
Quantum readiness starts with knowing where cryptography lives. Singapore’s 2026 milestones make discovery urgent, while SBOMs alone cannot show every algorithm, runtime setting or supplier dependency that may need a migration plan.
Cloudflare’s open-source coding-agent skill uses coverage-led hunting, independent validation, and structured evidence. Here is what the workflow can—and cannot—establish.
AI can help analysts navigate compiled software, but a decompiler output is not a vulnerability report. See how REA changes analysis, why reverse- engineering agents need protection, and how teams can validate findings.
An editorial guide to security MCP integrations for AI-assisted development: repository findings, scanning, web testing, supply chain analysis, and cloud security.
How specialized attack agents share context, challenge hypotheses, and independently verify attack paths inside the Plexicus Proof-Driven AppSec workflow.
A complete guide to application security in 2026, from secure design and software supply chains to testing, exploit validation, remediation, and Proof-Driven AppSec.
A fruit-fly connectome offers a vivid test of a security principle: a demo is not proof until controls show what the advertised system contributes.
DevDay 2026 connected persistent agents, cloud coding, plugins, events, and shared work. Here is what shipped, what is still coming, and where AppSec boundaries lie.
Opus 5.5 motion-graphics demos reveal an agentic loop: plan, write code, run it, inspect, revise. Claude cybersecurity now depends on verification keeping pace.
Jev AI returns typed decisions instead of prose. That could change where semantic judgment fits in security workflows, if teams keep policy, fallbacks, verification, and human review.
AI can remove repetitive AppSec work without removing accountability. Learn how to decide what to automate, what to augment, and when a security decision should be escalated to a person.
安全工具因其嘈杂的障碍而声名狼藉。当开发人员推送代码,而CI/CD管道因附带500页PDF报告而失败时,他们的自然反应不是修复问题,而是忽视它们或强制合并代码。
在本指南中,您将学习如何超越手动修补,构建一个使用AI驱动自动化来自动检测、优先处理和修复SQLi漏洞的工作流程。
如果您今天正在构建或运行软件,您可能正在同时处理微服务、无服务器功能、容器、第三方包以及大量的合规性检查项。每个活动部件都会产生自己的发现、仪表板和愤怒的红色警报。很快,风险可见性就像在凌晨2点的旧金山雾中驾驶——您知道危险就在外面,但您看不太清楚。
Plexicus is Proof-Driven AppSec: validated findings, contextual understanding, and reviewed remediation — anchored in evidence, scoped with you.