[osterverder]

thx for the tip, checking

[ResPublica]

Private end-to-end encrypted contact info:

simplex https://smp17.simplex.im/a#EkX4rl8mOtFuY...9sQN-gK5H4
xmpp omemo 58c6b966 7877eef9 11a922be d2cb6782 a728e522 0a2c796c 8a2ef41d 97996d69 [email protected]
email [email protected]
gpg 7637 C57E 4FF5 6E4A 9642 D410 F4CA 4D19 BFF3 0EBF

[ResPublica]

Private end-to-end encrypted contact info:

simplex https://smp17.simplex.im/a#EkX4rl8mOtFuY...9sQN-gK5H4
xmpp omemo 58c6b966 7877eef9 11a922be d2cb6782 a728e522 0a2c796c 8a2ef41d 97996d69 [email protected]
email [email protected]
gpg 7637 C57E 4FF5 6E4A 9642 D410 F4CA 4D19 BFF3 0EBF

[Khika7989]

thanx

[hulakaka]

thanks

[Ceriotari]

Hello DarkForums Community,
‎ ‎
Today we are selling Kafene customer DataBase, a lease-to-own company based in New York City. Thanks for reading and enjoy!



Kafene is a New York–based fintech that provides AI-driven lease-to-own financing at the point of sale for non-prime and underbanked consumers who are typically declined by traditional credit and BNPL providers. It operates a B2B2C embedded finance model, integrating into retailer checkout (online and in-store) so merchants—primarily in furniture, appliances, electronics, tires/auto repair, and jewelry—can approve more customers, increase basket size, and capture subprime demand. Kafene uses real-time underwriting with thousands of alternative data signals, instant approvals, recurring payment servicing, and ownership transfer at lease completion. Revenue comes from merchant fees, lease margins, and servicing income. On the partner side, its most important distribution integration is with LendPro’s multi-lender POS platform, which embeds Kafene into a broader financing waterfall; it also relies on debt facilities (e.g., Credit Suisse, Hudson Cove Capital) to fund leases and is backed by VCs including Valar Ventures, Third Prime, Global Founders Capital, Upper90, Company Ventures, and Uncorrelated Ventures. Strategically, Kafene positions itself as AI financing infrastructure for non-prime embedded commerce, competing with Progressive Leasing, Acima, Affirm, Klarna, After Pay, Sezzle, Splitit, Katapult, and Snap Finance while differentiating through tech-first underwriting and merchant integrations. Key growth signals include $100M+ sales within its first three years, expanding merchant network, and omnichannel POS coverage, with forward focus on new verticals (auto services, elective healthcare, broader durable goods) and deeper embedded finance partnerships. Core risks include regulatory scrutiny of lease-to-own models, credit loss sensitivity in downturns, merchant concentration, and BNPL players moving down-market.

The breached data encompasses:
Application and lease identifiers; merchant and store information including IDs, categories, fees, funding dates, amounts, statuses, and associated sales personnel; and the applicant’s full profile, including name, date of birth, address, email, phone number, income details, and application status with any decline reasons. It also includes credit and underwriting fields such as credit and Vantage score ranges, internal risk scores, grades and tiers, pricing tiers, program tags, and approved amounts, along with bank verification results containing bank names, routing and account numbers, and related response codes. In addition, the dataset contains either the last 4 Social Security numbers or the entire SSN for most customer records, and KYC artifacts comprising government-issued identification images or scans and selfie verification pictures, as well as references to internal company and customer document repositories and components of the AI-driven loan assessment framework.

On mid Feb 2026 Kafene was notified of the data breach incident; however as of Feb 25 it remains unclear whether the company truly cares about their customers safety as they've yet to publicly disclose the breach.

Sample Records (SSN, BANKING INFO, CREDIT SCORE, AND OTHER IDENTIFIERS):


Due to the amount of data points per person you'll be able to order records per your specific target profile. We'll help you find the exact profiles you need or discover patterns and relationships between desired data points of your interest.

Here is a detailed summary of the dataset (14 .png files and a .txt file, which detail major Banks, Age Range, States, Credit Profiles, etc):

https://anonfilesnew.com/s/H8tXquTSns1

https://www.virustotal.com/gui/file/4300.../detection

We would like to remind all potential buyers that since the breach is yet to be publicly disclosed by the company, customers affected currently remain unaware and thus are completely unprotected to any potential offensive use of their data. 

Contact for further inquiry:

SimpleX: https://smp17.simplex.im/a#EkX4rl8mOtFuY...9sQN-gK5H4
Xmpp: [email protected] (through OMEMO only)
OMEMO-key: 58c6b966 7877eef9 11a922be d2cb6782 a728e522 0a2c796c 8a2ef41d 97996d69
e-mail: [email protected]
pgp pub-key-fp: 7637 C57E 4FF5 6E4A 9642 D410 F4CA 4D19 BFF3 0EBF

[riza2jz]

lets see

[four544]

ggoood

[a531875]

asdsadsadsadsadsadsa

[bryanftwbl]

thanks vro