EchoLeak: The Zero-Click Microsoft Copilot Exploit That Changed AI Security
AI tools like Microsoft 365 Copilot are changing how organizations work, but they are also introducing new security risks that are harder to detect and even harder to defend.
One of the most significant examples to date is EchoLeak, a critical vulnerability discovered in early 2025 by researchers at Aim Security. Tracked as CVE-2025-32711, this zero-click exploit could silently steal sensitive business data using nothing more than a single email.
Unlike traditional phishing or malware attacks, EchoLeak required no interaction from the victim. The vulnerability relied on prompt injection, manipulating the AI assistant to retrieve and leak data without triggering alerts or suspicion.
Breach detection in AI environments now averages 290 days, which is nearly three months longer than traditional systems. EchoLeak showed how exposed enterprise AI has become.
As more organizations adopt platforms like Microsoft Copilot, the interconnected nature of these systems creates complex attack surfaces that traditional tools are not designed to monitor. EchoLeak demonstrated a new category of threats.
What Made EchoLeak So Dangerous?
EchoLeak stood apart from conventional cyberattacks by eliminating the need for user interaction.
This was a true zero-click vulnerability: no malicious links to click, no infected files to download. Just one crafted email was enough. Once delivered, the exploit relied entirely on normal Copilot usage to trigger.
At its core, EchoLeak was an elegant chain of prompt injection and context hijacking that turned Microsoft 365 Copilot into a silent accomplice in AI-driven data exfiltration.
Here’s how it worked:
Step 1: The Trojan Horse Email
The attacker sends a legitimate-looking business email, such as an Employee Onboarding Guide or a Q4 Planning Document.
Embedded within the body of the email are cleverly disguised instructions. To a human, the text appears benign. But to Copilot’s AI, these are operational prompts, designed to be acted upon later.
Step 2: The Patient Wait
The email remains idle in the victim’s inbox. Days or weeks later, the user might prompt Copilot with a query like “Tell me about our onboarding process.”
In response, Copilot’s Retrieval-Augmented Generation (RAG) engine selects the original email as relevant context.
Step 3: The Contextual Hijacking
As Copilot processes the email content, the hidden prompts spring into action. The AI unintentionally executes these commands, causing it to scan the user’s emails, files, and internal chat logs for sensitive information turning it into an unwitting insider threat.
Step 4: The Invisible Theft
Finally, Copilot inserts the stolen data into what appears to be a harmless Markdown link or image reference. When rendered, the link initiates a background request to an attacker-controlled server.
There are no alerts, no user warnings, just a broken image icon or invisible request that quietly leaks corporate secrets.
EchoLeak combined prompt injection, context misuse, and output bypass to exploit Copilot’s core design.
The result was a near-undetectable method for exfiltrating sensitive business data, with no indication to the user that anything was wrong.
The Technical Mechanics Behind EchoLeak
What made EchoLeak so effective (and alarming), was how it bypassed multiple layers of Microsoft’s built-in security within the Copilot architecture.
Rather than relying on a single point of failure, the exploit combined several tactics that worked together to evade detection and leak data.
- AI Prompt Injection
The core of the attack hinged on injecting malicious prompts that were cleverly masked as regular text.
Copilot’s safety filters missed the prompts because they resembled ordinary business text. - Output Filter Bypass
Once triggered, Copilot’s response was designed to appear legitimate. However, researchers found that Copilot did not consistently sanitize certain Markdown formats.
The flaw let attackers hide stolen data in links and images that Copilot failed to filter. - Content Security Policy Evasion
Even more concerning, the attackers discovered that Microsoft’s own services, like Teams and SharePoint, could be misused as trusted intermediaries.
By routing outbound traffic through these platforms, they sidestepped browser-level security controls that would normally block external data transmissions.
Real-World Impact
In their proof-of-concept, researchers demonstrated just how far-reaching the consequences of EchoLeak could be.
The vulnerability enabled the exfiltration of sensitive assets, including API keys, confidential project documents, and internal conversation snippets – all without the user noticing anything unusual.
The exploit functioned silently in the background, requiring no clicks, downloads, or additional software. It was effective across multiple Copilot sessions, meaning an attacker could maintain access over time simply by relying on the victim’s normal use of the AI assistant.
This made EchoLeak not only stealthy, but also persistent: a rare combination in exploit design.
Microsoft’s Response and Mitigation Efforts
To Microsoft’s credit, the response to EchoLeak was swift and decisive. After receiving a private disclosure from Aim Security in January 2025, the company took the following steps:
- Assigned the issue a critical CVSS score of 9.3, underscoring its severity
- Developed and rolled out server-side fixes by May 2025, without requiring any customer action
- Reported no evidence of exploitation in the wild prior to patch deployment
- Introduced enhanced Data Loss Prevention (DLP) controls, giving organizations greater ability to define which documents and communications Copilot is permitted to access
Because Copilot operates as a cloud-based AI assistant, Microsoft was able to patch the vulnerability at the platform level. This allowed for a coordinated, infrastructure-wide fix without needing to involve end users or IT teams.
The EchoLeak case has since become a reference point for how to respond effectively to emerging threats in AI-integrated environments.
Why EchoLeak Matters for Every Organization
EchoLeak was not just another vulnerability. It marked a turning point in how we understand the security risks of AI-powered platforms.
As large language models and assistants like Microsoft Copilot become embedded in business operations, their access to high-value data makes them an increasingly attractive target for cybercriminals.
The incident exposed a deeper architectural challenge.
AI systems are designed to be helpful, following instructions based on contextual understanding. But they are not yet capable of consistently distinguishing between legitimate user requests and malicious prompts hidden inside seemingly harmless data.
This inability to assess intent is a critical blind spot in current-generation AI tools.
Key Lessons for Security Teams
EchoLeak provides several clear lessons for anyone responsible for securing environments that include AI systems:
- AI Requires AI-Specific Defenses
Traditional cybersecurity controls do not address vulnerabilities like prompt injection, context hijacking, or AI-driven data leaks.
Security strategies must evolve to include LLM-specific safeguards.
- Trust Boundaries Must Be Reconsidered
Just because data exists within a secure environment does not mean it is safe for unrestricted AI access.Organizations must define and enforce contextual trust boundaries for AI tools.
- Output Validation Is Non-Negotiable
AI-generated content must be screened for data leakage vectors, especially when producing dynamic elements like links, images, or embedded metadata. - Layered Security Still Works
A well-architected defense in depth model can mitigate complex AI threats. Combining data classification, prompt filtering, network monitoring, and AI-specific DLP helps avoid single points of failure.
Looking Ahead: Preparing for the Next Wave
While Microsoft has addressed the EchoLeak vulnerability, it likely won’t be the last of its kind. As AI continues to integrate into daily workflows, attackers will keep evolving their tactics to manipulate these systems in subtle and sophisticated ways.
The good news? The security community is responding and learning fast. EchoLeak has already accelerated research into AI threat detection, prompt filtering techniques, and LLM-aware monitoring tools. Organizations are beginning to understand that deploying AI safely requires the same strategic oversight applied to any powerful enterprise technology.
The most important takeaway? AI assistants are tools, not oracles. They must be treated with the same discipline applied to other privileged systems: closely monitored, properly configured, and continuously updated to reflect the evolving threat landscape.
EchoLeak is a warning. In the age of AI, helpfulness can be weaponized. The only way to stay ahead is to remain proactive, informed, and intentional in how we design, deploy, and defend our AI systems.