Cases › security breach › LR-2026-0336
EchoLeak zero-click prompt injection exploit in Microsoft 365 Copilot
Preliminary Why: Publisher not yet named · subject to change
Developing: a major or severe case captured in the last 72 hours. Later changes are logged on the corrections page.
Status: action reported, no fix
No source states: loss or records, agent tool, could do, deployer, industry.
Severity major: Test: live production compromise. Fact: a real-world zero-click exploit against a production LLM system.
The system was Microsoft 365 Copilot, a large language model assistant used in enterprise workflows. A researcher case study describes EchoLeak (CVE-2025-32711), a zero-click prompt injection vulnerability in which a single crafted email led to remote, unauthenticated data exfiltration. The exploit chained several bypasses: evading the XPIA classifier, circumventing link redaction with reference-style Markdown, exploiting auto-fetched images, and abusing a Microsoft Teams proxy allowed by the content security policy. The chain achieved privilege escalation across LLM trust boundaries without user interaction. The paper analyses why existing defenses failed and recommends engineering mitigations. The sources do not state when the exploit occurred, how it was detected, or what changes followed in production.
What happened
What was done
Risks
Primary50 incidents
Rising: 6 vs 2.8 a week
Read from the sources; not yet reviewed by a person.
Controls
HarnessNot effective (bypassed) Prompt-injection detection
ApplicationNot effective (bypassed) Output filtering and redaction
Control failure chain
L1 · ModelMicrosoftModel provider
No source mentions a control at this layer.
Model version not linked to a model card.
L2 · HarnessHarness not namedAgent framework vendor
Other controls for this risk at this layer, not mentioned in the sources: Outside content treated as data, not instructions, Confirmation after untrusted input, Validation of tool inputs and outputs, Tool allow-list.
L3 · ApplicationDeployer not namedDeployer
Other controls for this risk at this layer, not mentioned in the sources: Human approval for high-impact actions, Least-privilege access for the agent, Segmentation of agent components, Alerts on unusual tool use.
L4 · Infrastructure / targetOrganisation hit
No source mentions a control at this layer.
EffectiveNot effectiveNot effective (bypassed)Did not existNot stated in sourcesNot yet checkedAttacker's ownOrder: model · harness · application · target
Controls for this risk: result in this incident
| Control | Part of the system | Result |
|---|---|---|
| Prompt-injection detection | L2 Harness | Not effective (bypassed) |
| Tool allow-list | L2 Harness | Not stated in sources |
| Confirmation after untrusted input | L2 Harness | Not stated in sources |
| Outside content treated as data, not instructions | L2 Harness | Not stated in sources |
| Validation of tool inputs and outputs | L2 Harness | Not stated in sources |
| Output filtering and redaction | L3 Application | Not effective (bypassed) |
| Least-privilege access for the agent | L3 Application | Not stated in sources |
| Human approval for high-impact actions | L3 Application | Not stated in sources |
| Segmentation of agent components | L3 Application | Not stated in sources |
| Alerts on unusual tool use | L3 Application | Not stated in sources |
Similar incidents
Evidence
- Cause hostile input carried instructions
- What set it off hidden instructions in its input
No source states: how it was caught, when it happened, when it was found, how many records were exposed, the direct loss, a count of the other parties affected, any court case.
Show every field, with its source and grade
The AI system
What happened
Impact
Notes on gaps
The 2025-11-23 date is the paper's publication date, not an incident date, so the timeline is empty. The paper recommends mitigations but reports no changes Microsoft made, and the caught step is not stated.
LR-2026-0336 · version 1 · published 2026-11-01 after automatic checks; not yet checked field by field by a person · JSON