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2 posts

• Gradient Inversion Attacks: Reconstructing Private Training Data from Model Updates

  Gradients are not safe summaries of training data. In federated learning and fine-tuning pipelines where model updates are shared, a malicious aggregator can run gradient inversion to recover original training samples with alarming fidelity — and the defenses have hard limits.

  Jul 4, 2026 federated-learning privacy gradient-inversion differential-privacy training-data attack-defense

• Federated Learning Poisoning: The Aggregation Attack Surface

  FL aggregation is blind to participant intent. Malicious clients can embed backdoors or reconstruct private training data from gradients.

  Jul 1, 2026 federated-learning poisoning-attacks backdoor privacy threat-modeling defense-patterns gradient-attacks differential-privacy secure-aggregation