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Iran steps into US election 2024 with cyber-enabled influence operations

A white ballot box with white squares and text 2024 US Election on a blue background.

Overview

Foreign malign influence concerning the 2024 US election started off slowly but has steadily picked up pace over the last six months due initially to Russian operations, but more recently from Iranian activity. This third election report from the Microsoft Threat Analysis Center (MTAC) provides an update on what we’ve observed from Russia, Iran, and China since our second report in April 2024, “Nation-states engage in US-focused influence operations ahead of US presidential election.”

Over the past several months, we have seen the emergence of significant influence activity by Iranian actors. Iranian cyber-enabled influence operations have been a consistent feature of at least the last three US election cycles. Iran’s operations have been notable and distinguishable from Russian campaigns for appearing later in the election season and employing cyberattacks more geared toward election conduct than swaying voters. Recent activity suggests the Iranian regime—along with the Kremlin—may be equally engaged in election 2024.

MTAC continues to examine authoritarian content to detect the malicious use of generative AI. This effort supports Microsoft’s commitment to the Tech Accord to Combat Deceptive Use of AI in 2024 Elections. Since our last report in April 2024, MTAC published a report regarding Russian influence operations to undermine the 2024 Summer Paris Olympics in which Storm-1679 has repeatedly utilized generative AI in its campaigns to little effect. In this installment, MTAC identifies a Russian and a Chinese actor that have employed generative AI—but with limited to no impact. In total, we’ve seen nearly all actors seek to incorporate AI content in their operations, but more recently many actors have pivoted back to techniques that have proven effective in the past—simple digital manipulations, mischaracterization of content, and use of trusted labels or logos atop false information.

Read the full report to learn more.

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