A single attacker using AI agents pulled emergency dispatch records covering seven Taipei districts, researchers at Acronis's Threat Research Unit said last week.
Acronis's core findings
Researchers at Acronis's Threat Research Unit recovered an operational attack platform that held more than 90,000 files tied to a single operator. The repository contained agent conversations, the attacker's command history, hacking tools, credentials, and stolen victims' data. Acronis watched the operation for 12 days and captured an exchange from July 25 that shows the attacker actively directing the system.
The unit says the evidence makes it "highly confident" the intrusion was run by one person based in Hualien City, Taiwan. That attribution rests on mistakes the attacker made while attempting to hide his identity — including reuse of a single identity across both legitimate business artifacts and the attack servers: a GitHub profile, a logo, an SSH key name, and an email address. The attacker's home IP address also appeared during an SSH session in one of his Grok conversations, the researchers report.
How BOSSAI worked — agent architecture and "abliterated" models
The attacker assembled a system Acronis calls BOSSAI: 12 AI agents were configured, with nine active in operations. Some agents maintained infrastructure; others scanned targets and executed attacks. The agents did not communicate directly with each other — the operator manually pasted one agent's output into another.
Commercial cloud models were used for much of the building work, with Grok identified as the main builder. When the attacker explicitly asked cloud models to perform attacks, Grok and Meta's MiniMax M3 refused and requested written proof of authorization. Grok did, however, make a single exception: it repaired a broken proof-of-concept script that the attacker then handed to an attack agent.
Where cloud models refused to participate, the attacker relied on "abliterated" models — versions of DeepSeek, GLM, and Qwen that ran locally with safety training removed. These ablated models carried much of the offensive workload; for example, Cursor ran an attack on a Taiwanese emergency-services site while operating such a model.
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See what we buildWhat the agents accessed: Taipei dispatch and patient records, Mexican phone lists, Thai and Taiwanese institutions
The most serious confirmed impact in Taiwan involved emergency-services data. The agents pulled dispatch records from a city's system for 119, Taiwan's emergency number for fire and ambulance services. Acronis says those records came from the system's API and include incident times, response types, case status, and street-level locations. The records are case logs, not live ambulance tracking.
Separately, the agents located a Taipei fire department platform exposing patient data dating back to 2018 — records that Acronis says included ECG readings and ambulance video footage and were accessible without a login. The researchers note those records were exposed, but their detailed account says only that the records were exposed rather than describing downstream use.
Beyond emergency services, the attackers used SQL injection to pull an account table from a Taiwanese lending firm, and to collect data from three Thai universities after selecting 489 potential targets across 45 institutions. In Mexico, Acronis documents the collection of roughly 206,800 home phone records containing names and addresses; those lists were assembled using government statistics, postal codes, and telecom authority data.
In total, the attacker aimed BOSSAI at hundreds of organizations across at least 11 countries. The agents collected data or accessed systems at about 10 organizations in Taiwan, Mexico, and Thailand. About 15 additional organizations were attacked without confirmed breaks, and at least eight other countries were scanned or had targets queued for attack but not yet executed when researchers examined the platform.
Techniques that failed and the limits of the operation
Acronis's analysis shows much of what BOSSAI found was already poorly protected: an open medical data port left exposed since 2018, a public-facing dispatch API, a lender platform with 16 SQL injection points, and universities running unpatched Oracle databases. The agents succeeded at scale because AI made it cheap to enumerate and reach many targets quickly.
But the agents often failed where basic defenses were in place. They could not pierce endpoints that enforced logins, paywalls requiring valid sessions, or properly filtered inputs. The agents also produced errors: one scanning tool invented CVEs and more than half of its high and critical findings were false positives or misclassified, and the main attack agent reported results that the researchers later determined had not occurred.
Acronis also lists nine IP addresses and nine domains tied to the attacker's setup in its indicator list; the entry notes neither their current activity status nor detailed roles for most of them.
What this means for Taipei emergency services, Thai universities, and a Taiwanese lender
- Taipei emergency services: Authorities and incident responders should treat the reported exposure of dispatch logs and the 2018 patient platform as operationally sensitive — dispatch case records and medical files including ECGs and ambulance video footage are the kinds of data that demand urgent containment and access controls. The researchers do not state whether affected organizations or Taiwan's authorities were notified, or whether data remain reachable.
- Thai universities: The universities that were targeted via SQL injection reflect common application-layer weaknesses; the incident underscores the need to patch and audit legacy database systems, especially where Acronis observed unpatched Oracle installations served as an attack vector.
- Taiwanese lender: The documented account-table extraction and the lender's 16 SQL injection points point to immediate remediation priorities — input validation, prepared statements, and targeted code reviews — because the attackers successfully harvested account data via straightforward SQL exploitation.
For all parties, the Acronis picture is stark: an individual operator, leveraging a mix of cloud builders and weaponized local models, automated reconnaissance at scale and harvested data where basic protections were absent. The operation exposes how cheaply and quickly attackers can chain AI-enabled tooling into organized campaigns — but also where standard security controls still hold firm.
