Mitigating risks from malicious AI sidebar extensions

AI sidebar extensions add conversational assistants and research helpers directly to the browser. They speed up work, but they also widen the attack surface. I will show the concrete threats and give hard, practical controls you can apply today. No theory. No fluff.

Threat Landscape

Overview of AI sidebar extensions

AI sidebar extensions run code inside the browser and call external AI APIs. They often request broad permissions, such as host access to all sites, cross-origin requests, or native messaging to local processes. That access lets an extension read page content, intercept form data, or inject scripts into sites you visit. Some extensions embed third-party AI models and handle sensitive content on behalf of the user. Treat those flows like any service that touches secrets.

Common tactics used by attackers

Malicious extensions reuse familiar tactics but with new vectors. Watch for:

• Script injection into page DOMs to alter AI prompts or display fake assistant responses.
• Command injection delivered as code blocks that appear as benign output from an assistant.
• OAuth abuse where the extension requests wide scopes and exchanges tokens with attacker-controlled endpoints.
• Native messaging to spawn local processes or run shell commands.
• Data exfiltration through batched requests, DNS tunnelling, or WebSocket callbacks.

A specific high-risk permission is host access to all sites, combined with native messaging. That mix lets an extension read a page with a credential prompt and hand it to a local agent or an external server.

Recent incidents involving malicious extensions

Researchers have demonstrated how attackers can replace legitimate sidebars with manipulated versions that return malicious instructions. In tests, an assistant gave a command line that would have opened a reverse shell when pasted and executed. Those proof-of-concept attacks show two things. First, a sidebar that can craft executable instructions is a dangerous asset in the wrong hands. Second, standard extension stores and default user consent are insufficient to stop clever attackers.

Prevention Strategies

Implementing zero-trust protocols

Treat browser-side AI as an untrusted service. Apply zero-trust controls that assume compromise. Practical moves:

• Restrict extension installs to a managed allow-list. On Windows, use Group Policy for Chrome and ADMX for Edge; on macOS use configuration profiles or MDM.
• Limit high-risk permissions: disallow “access to all sites”, native messaging, and host-wide content script injection except for trusted extensions.
• Enforce network segmentation. Place sensitive systems on separate networks and block browser-originated traffic from reaching internal APIs.
• Apply principle of least privilege to OAuth. Block token exchange flows from browser extensions unless the extension is vetted and signed.
• Use browser isolation for risky browsing sessions. Keep sensitive logins off commodity browsers that allow arbitrary extensions.

These are zero-trust protocols in practice: verify every request, minimise privileges, and isolate sensitive assets from general web browsing.

CISO guidelines for browser security

I write CISO guidelines bluntly. Start with policy and technical enforcement:

• Define an extension policy that lists allowed extensions and permission sets.
• Require code review or third-party attestation for any extension used for work that touches secrets.
• Mandate endpoint protections: EDR with browser-oriented telemetry, DNS logging, and proxy inspection.
• Track OAuth grants centrally. Log and revoke suspicious tokens quickly.
• Set expiry for long-lived tokens issued to extensions, and rotate client secrets.

Have a high-risk device profile. If a device runs unvetted extensions, treat it as untrusted and limit access to critical systems.

Best practices for auditing extensions

Audit code before approval. Steps:

1. Install the extension unpacked and read manifest.json. Flag broad host permissions, nativeMessaging, or background scripts.
2. Grep source for eval, Function(, new Worker, websocket, or fetch calls to external domains.
3. Run static analysis and dependency checks against known CVEs.
4. Execute the extension in an isolated VM and record network traffic. Look for unexpected outbound connections, DNS requests, or credential exfiltration.
5. Check update channels. Some extensions fetch remote code at runtime. Verify update endpoints and signatures.

Keep an audit log with timestamps and the hashes of approved extension builds. Re-audit after each update.

Importance of user education

Users make decisions that technical controls miss. Train them on these points:

• Never paste random command lines from an assistant into a shell without inspection.
• Treat AI assistant output as untrusted text. Verify commands against trusted documentation.
• Reject extension requests that ask for host-wide permissions or native messaging.
• Report unexpected browser prompts and unknown OAuth consent screens immediately.

Run short, scenario-based drills. Give one example of a malicious output and show the safe alternative steps.

Monitoring and incident response

Assume compromise and watch for signs:

• Sudden increase in DNS queries from browsers to unknown domains.
• Unusual OAuth token grants or login attempts from new IP ranges.
• Spikes in calls to external AI APIs from devices that do not normally use them.
• Creation of unexpected local processes from browser contexts.

Response checklist:

• Isolate the affected device from the network.
• Disable and remove the suspect extension.
• Revoke browser-held OAuth tokens and rotate any exposed credentials.
• Collect browser profile files and extension code for forensic review.
• Check for persistence via native messaging hosts or scheduled tasks.
• Restore from a known-good image if indicators of compromise include local shells or unknown services.

Document each incident and the remediation steps. Use those notes to tighten extension policies and update the allow-list.

Final takeaways
Treat AI sidebar extensions like apps that can run arbitrary code in the browser and touch sensitive data. Block broad permissions, enforce an allow-list, audit code, and monitor for odd network or token activity. Train people to treat AI output with scepticism, and keep hardened devices separate from casual browsing. Those steps cut most of the realistic risk without sacrificing useful tooling.