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Alleged AI-Powered Call Center Breach Exposes Over 10 Million Conversations in the Middle East

3 news reports Snapshot 7 Sep 2026

In brief

An AI system built by Unnamed Ai Call Center Platform Provider and deployed by Cybercriminals allegedly harmed Privacy, Enterprise Clients and 1 other.

Risk domain
Privacy & Security Compromise of privacy by obtaining, leaking or correctly inferring sensitive information
Occurred
Coverage
3 reportsOct 2024

What happened

An AI-powered call center platform in the Middle East reportedly experienced a significant data breach, allegedly exposing over 10 million conversations between consumers, operators, and AI agents. Attackers allegedly accessed the platform’s management dashboard, stealing sensitive data, including national ID documents. The breach poses reported risks such as phishing, identity theft, and social engineering attacks. The stolen data was reportedly listed for sale on the dark web.

Laws that address this harm

Policy angle: Classified under Privacy & Security (Compromise of privacy by obtaining, leaking or correctly inferring sensitive information) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case.

Matched from the record's risk domain and country to the instruments recorded here. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (3)

Titles link to the original publisher; report text is not reproduced here.

  1. Cybercriminals Are Targeting AI Agents and Conversational Platforms: Emerging Risks for Businesses and Consumers
    resecurity.com · Resecurity
  2. Over 10m Conversations Exposed in AI Call Center Hack
    infosecurity-magazine.com · Alessandro Mascellino
  3. Millions of conversations leaked after AI call center hacked
    techradar.com · Sead Fadilpašić

Who was involved

Alleged deployer
Cybercriminals
Alleged harmed party
Privacy, Enterprise Clients, End Users Of Undisclosed Middle Eastern Ai Powered Cloud Call Center Platform

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
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Sectors
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Countries
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Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 2.1.

  • Risks to privacy

    "General- purpose AI models or systems can ‘leak’ information about individuals whose data was used in training. For future models trained on sensitive personal data like health or financial data, this may lead to partic...

    International Scientific Report on the Safety of Advanced AI (Bengio2024)

  • Risks to privacy

    "General- purpose AI systems can cause or contribute to violations of user privacy. Violations can occur inadvertently during the training or usage of AI systems, for example through unauthorised processing of personal d...

    International AI Safety Report 2025 (Bengio2025)

  • Private Training Data

    "As recent LLMs continue to incorporate licensed, created, and publicly available data sources in their corpora, the potential to mix private data in the training corpora is significantly increased. The misused private d...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Association in LLMs

    "Association in LLMs refers to the capability to associate various pieces of information related to a person. According to [68], [86], given a pair of PII entities (xi , xj ), which is associated by a model F. Using a pr...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy Leakage

    "Privacy Leakage means the generated content includes sensitive personal information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Memorization in LLMs

    "Memorization in LLMs refers to the capability to recover the training data with contextual prefixes. According to [88]–[90], given a PII entity x, which is memorized by a model F. Using a prompt p could force the model...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy Leakage

    "The model is trained with personal data in the corpus and unintentionally exposing them during the conversation."

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy and regulation violations

    "Some of the broken systems discussed above are also very invasive of people’s privacy, controlling, for instance, the length of someone’s last romantic relationship [51]. More recently, ChatGPT was banned in Italy over...

    Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)

Incidents in the same risk subdomain

All incidents in this subdomain

Other incidents involving Cybercriminals

Source record: incident #906 on the AI Incident Database · all 3 reports