ATTACK METHODS
Attack Methods & Trends
We auto-classified the 471 incidents collected on this site by attack method, based on the wording of official disclosures. See how data is actually leaking, with counts and representative cases, alongside official Japanese statistics and the latest global threat reports.
Incidents by method (471 total)
Classification is automated from disclosure wording. Compound incidents are counted under the more specific method; incidents without a disclosed cause fall under "Under investigation".
| Method | Count | Share | Summary |
|---|---|---|---|
| Unauthorized access (method undisclosed) | 166 | 35% | Breached, but the technique was not identified or disclosed |
| Under investigation / not stated | 94 | 20% | Cause not disclosed |
| Supply chain attacks (via vendors & shared services) | 49 | 10% | Compromising the provider instead of the user |
| Ransomware | 46 | 10% | Encrypting data and demanding a ransom |
| Exploitation of vulnerabilities | 39 | 8% | Breaking in through holes in software and devices |
| Abuse of credentials | 28 | 6% | Logging in legitimately with leaked or guessed passwords |
| Misdirected sending & disclosure (human error) | 20 | 4% | Leaks caused by wrong recipients or exposure settings |
| Targeted email & phishing | 12 | 3% | Fake emails and sites that steal credentials |
| Misconfiguration & access-control gaps | 11 | 2% | Data left readable by anyone |
| Loss & theft | 5 | 1% | Physical loss of devices and media |
| System defects | 1 | 0% | Bugs that expose other users' data |
In October 2026 alone there were 219 disclosures, with supply-chain intrusions and undisclosed-method attacks surging.
Method-by-method explanation
Each method's mechanism, typical flow, targeted data, key countermeasures, and representative incidents from our collection.
Under investigation / not stated
94 incidentsAt the initial announcement the cause is listed as under investigation. Cases are reclassified as follow-ups clarify. Japan's disclosure-driven reporting means this share is high.
Observed techniques
Typical flow
- A possible leak is detected
- Investigation of cause and scope continues
- A confirmed follow-up is published
Targeted data: —
Key countermeasures: Prompt initial reporting, consultation with specialists(Protection guide)
Largest-impact examples
- Suno55,282,226 records・disclosed July 19, 2026
- EPARKリラク&エステ(PeakManager)22,180,000 records・disclosed September 23, 2026
- 手間いらず(宿泊予約管理システム)4,450,000 people・disclosed September 27, 2026
Shared services — reservations, e-commerce platforms, email delivery — and outsourcing vendors are attacked, and the damage cascades to every company that entrusted them with data. Japan saw this pattern repeatedly in autumn 2026, with single incidents affecting tens of millions of records.
Observed techniques
Typical flow
- The service provider's system is compromised
- Data aggregated from many client companies is stolen at once
- Client companies issue disclosures and notifications one after another
Targeted data: Customer and transaction data of many companies held by the provider
Key countermeasures: Minimize data you hand over, vet providers, encrypt and shard on your side(Protection guide)
Largest-impact examples
- 第一興商(ビッグエコー等)8,631,000 records・disclosed October 7, 2026
- 旭化成セラピューティクス(Pharma DIGITAL)514,000 people・disclosed October 5, 2026
- 大和証券220,000 records・disclosed October 4, 2026
Attackers who break in encrypt the data and demand payment in exchange for decryption and silence. Double extortion — also threatening to publish the stolen data — is now the norm; Japan logged a record 123 confirmed cases in the first half of 2026.
Observed techniques
Typical flow
- Initial access via vulnerabilities, stolen credentials, or email
- Steal credentials and move laterally; disable backups
- Exfiltrate data, then encrypt it and demand payment (double extortion)
Targeted data: Customer and financial records; leaked and resold after theft
Key countermeasures: 3-2-1 backups, MFA, emergency contact plans, recovery drills(Protection guide)
Largest-impact examples
- ライドオンエクスプレス(『銀のさら・釜寅・すし上等』公式サイト・公式アプリ)6,500,000 records・disclosed October 12, 2026
- アフラック生命保険4,400,000 people・disclosed June 29, 2026
- アサヒグループホールディングス1,525,000 records・disclosed July 16, 2026
Attackers enter through unpatched vulnerabilities in public web applications and edge devices such as VPNs. Worldwide, vulnerability exploitation is now the top initial access vector (31%), and delayed patching translates directly into breaches.
Observed techniques
Typical flow
- Scan internet-facing services for vulnerabilities
- Exploit a known or zero-day flaw and plant a web shell
- Escalate privileges, move laterally, and reach the database
Targeted data: Customer databases behind public applications
Key countermeasures: Rapid patching, inventory of internet-facing assets, WAF(Protection guide)
Largest-impact examples
- Helpfeel(Gyazo)23,620,000 records・disclosed September 15, 2026
- Eストアー(ショップサーブ)23,356,000 people・disclosed October 15, 2026
- アドベンチャー(スカイチケット)14,640,000 records・disclosed October 9, 2026
Attackers sign in with username-password pairs leaked in earlier breaches (credential stuffing) or found via dictionary attacks. Password reuse is the single biggest multiplier of damage.
Observed techniques
Typical flow
- Reuse credential lists from past breaches
- Try the same pairs on other services
- Hijack the accounts that authenticate successfully
Targeted data: Member accounts, points and payment data
Key countermeasures: Unique passwords per service, MFA, anomaly detection on logins(Protection guide)
Largest-impact examples
- 日本経済新聞社(日経)1,830,000 records・disclosed October 15, 2026
- チャーム本店370,000 records・disclosed August 31, 2026
- CAMPFIRE225,846 accounts・disclosed June 1, 2026
Misdirected sending & disclosure (human error)
20 incidentsNot an attack but a mistake: mass emails sent without BCC, files uploaded with open access. Incidents occur every month. Volumes are small, but trust damage is large; training and pre-send checks work.
Observed techniques
Typical flow
- Send a mass email to wrong recipients (no BCC, etc.)
- Leave private data in a publicly visible state
- Third parties view or download it before anyone notices
Targeted data: Customer names and contact details
Key countermeasures: Multi-person review before sending, BCC rules, access reviews(Protection guide)
Largest-impact examples
- 京都サンガF.C.15,612 people・disclosed September 7, 2026
- 沖縄県立芸術大学207 people・disclosed October 1, 2026
- 大阪市総合生涯学習センター(メール)168 people・disclosed September 7, 2026
Emails impersonating real business partners or executives lure victims to fake sites where they enter IDs and passwords. Business email compromise (BEC) targeting finance staff causes payment-diversion losses.
Observed techniques
Typical flow
- Send a convincing business email or SMS
- Capture credentials on a fake login or application form
- Use the stolen credentials to enter the real system
Targeted data: Login credentials; payment and contract approval authority
Key countermeasures: Verify links before clicking, multi-person payment approval, MFA(Protection guide)
Largest-impact examples
- カインドオル(ECサイト)136,464 people・disclosed September 1, 2026
- Axcelead Drug Discovery Partners株式会社7,000 records・disclosed July 21, 2026
- 株式会社講談社3,812 records・disclosed August 2, 2026
Human-error methods — misdelivery, misconfiguration, loss, insider misuse, system defects — are counted in the table above. See the protection guide for mechanisms and countermeasures.
Last 6 months
| Month | Total | Unauthorized access | Supply chain attacks | Ransomware | Exploitation of vulnerabilities | Abuse of credentials | Under investigation / not stated |
|---|---|---|---|---|---|---|---|
| May 2026 | 23 | 6 | 0 | 6 | 2 | 4 | 4 |
| June 2026 | 26 | 8 | 1 | 6 | 3 | 3 | 4 |
| July 2026 | 23 | 8 | 3 | 4 | 1 | 1 | 3 |
| August 2026 | 36 | 11 | 1 | 5 | 4 | 3 | 10 |
| September 2026 | 67 | 26 | 5 | 1 | 8 | 4 | 15 |
| October 2026 | 219 | 84 | 34 | 9 | 12 | 9 | 46 |
Trends in Japan (2026)
Autumn 2026 brought Japan its largest recorded wave of data breaches and unauthorized access. NPA statistics show 123 confirmed ransomware cases in H1 2026 — a half-year record since counting began in 2020. Suspicious access detections reached about 13,700 per day (up ~50% year on year), and phishing reports topped 730,000.
The government declared cyberspace a state of emergency and ordered ministries, municipalities, and businesses to enforce basics (updates, strong passwords, supply chain checks). Authority to neutralize attacker tools under the Active Cyberdefense Law took effect October 1, 2026. Businesses can now consult the IPA's special unauthorized-access desk from the moment they suspect damage, and the PPC has issued alerts.
By technique, supply-chain cascades through shared services and vendors stand out domestically. Compromises of reservation systems, e-commerce builders, and clouds have hit hundreds of client companies and municipalities at once.
Global trends (2026)
Vulnerability exploitation is now the top initial access vector. Verizon's 2026 DBIR puts it at 31%, overtaking stolen credentials. Exploitation of VPNs and edge devices jumped from ~3% to 22% — slow patching of perimeter devices is a worldwide weakness. Phishing is flat at 16%, pretexting grew to 6% as a path into ransom and extortion, and ransomware is involved in 48% of all breaches.
AI-enabled attackers are surging. CrowdStrike's 2026 Global Threat Report ("The Evasive Adversary Wields AI") counts an 89% year-over-year increase. Average breakout time hit a record-fast 29 minutes, and pre-disclosure zero-day exploitation rose 42%. Ransomware variants sharing AI-generated code defects have been observed — defenders are being tested on containment speed.
AI agents now steal directly. In South Korea, AI tools are suspected in attacks on several banks, and security researchers reported an AI agent stealing about 600,000 credit card records. Cheaper attacks mean mid-sized and small businesses everywhere are becoming targets. The Chinese AI systems reported in the 2026 attacks including Japan's are covered in the next section.
AI Abused for Attacks — the Chinese Models "ARTEX" and "DeepSeek"
ARTEX (Chinese AI agent). In October 2026, an investigation by a Japanese company (a GMO subsidiary) confirmed that a Chinese AI tool, ARTEX, was used on all six servers behind a series of unauthorized accesses spanning roughly 80 Japanese companies in insurance, finance, and logistics. ARTEX originated as an open-source AI penetration-testing tool; industry-targeted operations against finance, retail, insurance, and e-commerce have been reported, and its abuse is confirmed or suspected in attacks on major Korean financial institutions and US companies. The developer withdrew it after the reports, but copies have spread and the threat persists. Multiple outlets report that a substantial share of Japan's autumn 2026 breach wave may be of this lineage — timing that matches the ~2.5× month-over-month surge in incidents we collected for October.
DeepSeek (Chinese open-source LLM). In July 2026, Palo Alto Networks' Unit 42 reported a Mandarin-speaking actor using DeepSeek via the "Hermes Agent" framework to run autonomous attacks combining AI-driven scanning of seven vulnerability classes with manual exploitation. Bloomberg (August 2026) reported that Chinese hackers have intensified activity since folding DeepSeek and other open-source models into their workflows. CSIS had already flagged DeepSeek's weak guardrails (jailbreak resistance, malware generation) in 2025: the pattern of cheap, loosely restricted Chinese models lowering the technical bar for attacks has persisted for over a year.
What the AI actually does. In every case, the AI handles preparation: scanning public services for vulnerabilities, generating and tuning attack code, and selecting targets — the final intrusion and theft still require human hands. The essentials of defense are unchanged: assume-compromise design (MFA, least privilege, log preservation, rapid detection). The AI era does not demote the basics.
Sources
- Incident data & classification: this site's collection (automated classification of disclosures). Breach database
- National Police Agency cyber threat alerts (October 2026): www.npa.go.jp and press reporting (Kyodo)
- Personal Information Protection Commission alert on large-scale breaches (October 7, 2026): www.ppc.go.jp
- Verizon 2026 Data Breach Investigations Report: verizon.com (PDF)
- CrowdStrike 2026 Global Threat Report: crowdstrike.com
- ARTEX (October 2026): Jiji Press, Yomiuri Shimbun, Nikkei, and Impress reportingJiji Press
- DeepSeek abuse: Palo Alto Networks Unit 42 "Autonomous AI Cyber Attack Campaign" (July 2026)Unit 42; CSIS "Delving into the Dangers of DeepSeek" (February 2025)