Gemini Prompt Injection Exposes Calendar Data

Key Takeaways

• An indirect prompt injection vulnerability in Google’s Gemini LLM was disclosed that exploited Calendar integration. 
• By embedding malicious prompts in Calendar invites, an attacker could cause the AI to exfiltrate private meeting details. 
• The flaw bypassed standard privacy controls and relied on the model’s interpretation of legitimate calendar context. 
• Google has since mitigated the issue following responsible disclosure.

When AI Misinterprets Trust: The Google Gemini Prompt Injection Incident

In January 2026, cybersecurity researchers disclosed a significant indirect prompt injection weakness in Google’s Gemini generative AI assistant that was integrated with Workspace apps like Google Calendar. The flaw allowed threat actors to craft calendar invites with hidden instructions that Gemini would later execute when users asked routine questions about their schedule, leading to the creation of new calendar entries containing summaries of private meetings accessible to attackers. (CSO Online)

What Happened

The vulnerability stemmed from the way Gemini processes contextual data from Google Calendar events. Researchers from Miggo Security found that by embedding carefully constructed text in the description of a calendar invite, an attacker could influence Gemini’s behavior when a user later asked about their schedule. Instead of merely summarizing events, Gemini would parse the malicious payload, create a new event with sensitive meeting details in the description, and surface that event such that attackers with visibility could read private data. (BleepingComputer)

Unlike conventional malware or code injection, this attack leveraged natural language understanding and the model’s trusted context ingestion, effectively weaponizing everyday artifacts like calendar invites to bypass privacy guardrails that are not designed to interpret embedded prompts. (Dark Reading)

Google confirmed the issue and has since released mitigations to address the prompt injection pathway. 

How the Breach Happened

The attack began with a crafted calendar invitation containing a benign-looking description that secretly included a malicious instruction written in natural language. When the victim—whose calendar was accessible to Gemini—later requested information about their schedule, the assistant ingested all associated data, including the embedded prompt. This triggered unintended behavior, causing Gemini to summarize and re-publish sensitive calendar details. 

Because the exploit worked through innocuous user interaction and leveraged contextual understanding rather than software code execution, traditional defenses like signature-based detection and input sanitization were ineffective. 

Why It Matters

This incident illustrates how AI integrations in productivity tools can be manipulated to expose sensitive organizational data without requiring malware or elevated privileges. In enterprise deployments where calendars contain strategic meeting details, disclosure of this information can lead to operational exposure or insider threat footholds. (Dark Reading)
Although mitigated, the flaw underscores that prompt injection variants can cross-application boundaries and bypass privacy controls—highlighting gaps in current AI safety practices. 

Business Impact Score: 6.0
Reasoning: Confirmed proof-of-concept with real data exposure potential in enterprise contexts, though no widespread exploitation is currently documented.

PointGuard AI Perspective

The Gemini prompt injection incident highlights a class of AI risk that goes beyond traditional software vulnerabilities: semantic manipulation through natural language context. As AI assistants become embedded in workflows across email, calendars, and enterprise apps, attackers will increasingly target the language interface itself to trigger unintended actions and data flows.

Organizations must augment conventional application security with AI-aware defenses that validate intent and provenance of natural language inputs, track how models consume contextual data, and enforce strict guardrails around sensitive data handling at runtime. Continuous testing for prompt injection resilience and monitoring for anomalous model behavior should be part of any mature AI security program.

PointGuard AI’s runtime AI governance capabilities are designed to surface and remediate these emerging attack surfaces by correlating AI context, user actions, and data access patterns into coherent, auditable trails that help defend against sophisticated prompt manipulation risks.

Incident Scorecard Details

Total AISSI Score: 5.8/10
Criticality = 7.0
Indirect access to sensitive enterprise data through AI misuse.

Propagation = 6.5
Attack relies on social engineering of calendar invites but could affect many users in shared environments.

Exploitability = 7.0
Requires only crafted invites and normal user interaction.

Supply Chain = 5.0
No third-party dependency exploited; leverages model behavior.

Business Impact = 5.0
Real data exposure vector; mitigations now deployed but exploitation could reveal sensitive organizational information.

Sources

• Google Gemini Prompt Injection Flaw Exposed Private Calendar Data via Malicious Invites — The Hacker News
  https://thehackernews.com/2026/01/google-gemini-prompt-injection-flaw.html
• Google Gemini flaw exposes new AI prompt injection risks for enterprises — CSO Online
  https://www.csoonline.com/article/4119029/google-gemini-flaw-exposes-new-ai-prompt-injection-risks-for-enterprises.html
• Gemini AI assistant tricked into leaking Google Calendar data — BleepingComputer
  https://www.bleepingcomputer.com/news/security/gemini-ai-assistant-tricked-into-leaking-google-calendar-data/
• Indirect prompt injection in Google Gemini enabled unauthorized access to meeting data — SiliconANGLE
  https://siliconangle.com/2026/01/19/indirect-prompt-injection-google-gemini-enabled-unauthorized-access-meeting-data/