[aziz123321]

i think it is very good

[feuj2luxe]

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

thanks

[vanhelsing27]

Merhaba DarkForums Topluluğu,
Bugün
New York merkezli bir kiralama-satın alma şirketi olan Kafene'nin müşteri veritabanını satıyoruz. Okuduğunuz için teşekkürler ve keyifli okumalar!



Kafene, geleneksel kredi ve BNPL sağlayıcıları tarafından genellikle reddedilen, düşük kredi notuna sahip ve bankacılık hizmetlerinden yeterince yararlanamayan tüketiciler için satış noktasında yapay zeka destekli kiralama-satın alma finansmanı sağlayan New York merkezli bir fintech şirketidir. Perakendecilerin (çevrimiçi ve mağaza içi) ödeme sistemine entegre olan B2B2C gömülü finansman modelini işletmektedir; böylece öncelikle mobilya, beyaz eşya, elektronik, lastik/oto tamir ve mücevher sektörlerindeki satıcılar daha fazla müşteriyi onaylayabilir, sepet büyüklüğünü artırabilir ve düşük kredi notuna sahip tüketicilerin talebini karşılayabilir. Kafene, binlerce alternatif veri sinyaliyle gerçek zamanlı kredi değerlendirmesi, anında onaylar, tekrarlayan ödeme hizmeti ve kiralama tamamlandığında mülkiyet devri kullanmaktadır. Gelir, satıcı ücretlerinden, kiralama marjlarından ve hizmet gelirlerinden elde edilir. Ortaklık tarafında, en önemli dağıtım entegrasyonu, Kafene'i daha geniş bir finansman akışına entegre eden LendPro'nun çoklu kredi veren POS platformuyla gerçekleşmektedir; ayrıca kiralama işlemlerini finanse etmek için borçlanma olanaklarına (örneğin, Credit Suisse, Hudson Cove Capital) güvenmekte ve Valar Ventures, Third Prime, Global Founders Capital, Upper90, Company Ventures ve Uncorrelated Ventures gibi risk sermayesi şirketleri tarafından desteklenmektedir. Stratejik olarak Kafene, teknoloji odaklı kredi değerlendirmesi ve satıcı entegrasyonlarıyla farklılaşırken, Progressive Leasing, Acima, Affirm, Klarna, After Pay, Sezzle, Splitit, Katapult ve Snap Finance ile rekabet eden, düşük kredi notuna sahip müşteriler için entegre ticarete yönelik yapay zeka finansman altyapısı olarak konumlanmaktadır. Önemli büyüme sinyalleri arasında ilk üç yılda 100 milyon doların üzerinde satış, genişleyen satıcı ağı ve çok kanallı POS kapsamı yer alırken, yeni sektörlere (oto servisleri, isteğe bağlı sağlık hizmetleri, daha geniş dayanıklı tüketim malları) ve daha derin entegre finansman ortaklıklarına odaklanmaktadır. Temel riskler arasında kiralama-satın alma modellerinin düzenleyici kurumlar tarafından incelenmesi, ekonomik durgunluk dönemlerinde kredi kaybına duyarlılık, satıcı yoğunlaşması ve BNPL (Şimdi Al Sonra Öde) oyuncularının daha düşük pazarlara kayması yer almaktadır.

İhlal edilen veriler şunları kapsamaktadır:
Başvuru ve kiralama tanımlayıcıları; kimlikler, kategoriler, ücretler, fonlama tarihleri, tutarlar, durumlar ve ilgili satış personeli dahil olmak üzere satıcı ve mağaza bilgileri; ve başvuru sahibinin adı, doğum tarihi, adresi, e-postası, telefon numarası, gelir bilgileri ve herhangi bir ret nedeni ile başvuru durumu dahil olmak üzere tam profili. Ayrıca, kredi ve Vantage puan aralıkları, dahili risk puanları, dereceler ve kademeler, fiyatlandırma kademeleri, program etiketleri ve onaylanan tutarlar gibi kredi ve sigorta alanlarının yanı sıra banka adları, yönlendirme ve hesap numaraları ve ilgili yanıt kodlarını içeren banka doğrulama sonuçlarını da içerir. Ek olarak, veri seti çoğu müşteri kaydı için ya son 4 Sosyal Güvenlik numarasını ya da tüm SSN'yi ve devlet tarafından verilen kimlik görüntüleri veya taramaları ve özçekim doğrulama resimlerinden oluşan KYC unsurlarını, ayrıca şirket içi ve müşteri belge depolarına ve yapay zeka destekli kredi değerlendirme çerçevesinin bileşenlerine referansları içerir.

Şubat 2026 ortalarında Kafene, veri ihlali olayından haberdar edildi; Ancak 25 Şubat itibariyle, şirketin müşterilerinin güvenliğini gerçekten önemseyip önemsemediği belirsizliğini koruyor, zira veri ihlalini henüz kamuoyuna açıklamadılar.

Örnek Kayıtlar (Sosyal Güvenlik Numarası, Bankacılık Bilgileri, Kredi Puanı ve Diğer Tanımlayıcılar):


Kişi başına veri noktası sayısı nedeniyle, belirli hedef profilinize göre kayıt siparişi verebileceksiniz. İhtiyacınız olan profilleri bulmanıza veya ilgilendiğiniz veri noktaları arasındaki kalıpları ve ilişkileri keşfetmenize yardımcı olacağız.

İşte veri setinin ayrıntılı bir özeti (büyük bankaları, yaş aralığını, eyaletleri, kredi profillerini vb. ayrıntıları içeren 14 .png dosyası ve bir .txt dosyası):

https://anonfilesnew.com/s/H8tXquTSns1

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

Tüm potansiyel alıcılara, veri ihlalinin şirket tarafından henüz kamuoyuna açıklanmadığı için etkilenen müşterilerin şu anda durumdan habersiz olduğunu ve bu nedenle verilerinin olası her türlü saldırgan kullanımına karşı tamamen korunmasız olduklarını hatırlatmak isteriz. 

Daha fazla bilgi için iletişime geçin:

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

Thx bro

[bluehemoth]

W leak, nice job

[marksa19]

niiice

[boneybons]

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

hh

[number2]

...............

[Xyra77]

Thanks for sharing

[eminemem3]

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

---

Thank you so much for your help Thank you so much for your help
Thank you so much for your help Thank you so much for your help