Alvin ISD is a dynamic learning institution dedicated to serving all 252 square miles of our district. Visit our website for more information on our great district!
Lovely Professional University (LPU) is an ASSOCHAM’s National Education Excellence Award-winning institution and has also been ranked as top Education Brand of India in Economic Times. LPU is a multi-disciplined university and offers 200+ programs in 40+ disciplines. These programs are recognized by the statutory bodies of the Government of India in diverse fields of higher education including National Council for Teacher Education (NCTE), Distance Education Council (DEC), Pharmacy Council of India (PCI), Council of Architecture (COA) and Bar Council of India (BCI). LPU has been created keeping the student aspiration and industrial requirement in mind. The infrastructure, curriculum, pedagogy and faculty work in synchronization to fulfil the motto and goal of the institution. The curriculum development involves multiple stages of refinement and one of the most important steps is the industry feedback. LPU has set the record for the highest placements in any of the North Indian universities three times in a row. Cognizant alone has taken 1900 students in three years from LPU. Presently LPU students are working worldwide with prestigious global companies like Google, Microsoft, Apple, Amazon and many more at salary packages of more than Rs one Crore. LPU’s infrastructure is unparalleled to any of the universities in India. It is a mini township. It has fantastic academic facilities, an eight-storied library and research block, hostel and accommodation facilities for over 20,000 students, a shopping mall, numerous eateries including brands like Domino’s and Café Coffee Day, plenty of workshop area, India’s first iMac Lab and various other facilities for students to grow and accomplish their goals. The university has recently invested hugely on its security systems and has stepped forward to become one of the safest campuses in the world.
Security & Compliance Standards Overview
No incidents recorded for Alvin ISD in 2025.
No incidents recorded for Lovely Professional University in 2025.
Alvin ISD cyber incidents detection timeline including parent company and subsidiaries
Lovely Professional University cyber incidents detection timeline including parent company and subsidiaries
Last 3 Security & Risk Events by Company
Sakai is a Collaboration and Learning Environment. Prior to versions 23.5 and 25.0, EncryptionUtilityServiceImpl initialized an AES256TextEncryptor password (serverSecretKey) using RandomStringUtils with the default java.util.Random. java.util.Random is a non‑cryptographic PRNG and can be predicted from limited state/seed information (e.g., start time window), substantially reducing the effective search space of the generated key. An attacker who can obtain ciphertexts (e.g., exported or at‑rest strings protected by this service) and approximate the PRNG seed can feasibly reconstruct the serverSecretKey and decrypt affected data. SAK-49866 is patched in Sakai 23.5, 25.0, and trunk.
pypdf is a free and open-source pure-python PDF library. Prior to version 6.1.3, an attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires parsing the content stream of a page using the LZWDecode filter. This has been fixed in pypdf version 6.1.3.
pypdf is a free and open-source pure-python PDF library. Prior to version 6.1.3, an attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires parsing the content stream of a page which has an inline image using the DCTDecode filter. This has been fixed in pypdf version 6.1.3.
Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to version 1.6.5, Authlib’s JWE zip=DEF path performs unbounded DEFLATE decompression. A very small ciphertext can expand into tens or hundreds of megabytes on decrypt, allowing an attacker who can supply decryptable tokens to exhaust memory and CPU and cause denial of service. This issue has been patched in version 1.6.5. Workarounds for this issue involve rejecting or stripping zip=DEF for inbound JWEs at the application boundary, forking and add a bounded decompression guard via decompressobj().decompress(data, MAX_SIZE)) and returning an error when output exceeds a safe limit, or enforcing strict maximum token sizes and fail fast on oversized inputs; combine with rate limiting.
OpenBao is an open source identity-based secrets management system. Prior to version 2.4.2, OpenBao's audit log did not appropriately redact fields when relevant subsystems sent []byte response parameters rather than strings. This includes, but is not limited to sys/raw with use of encoding=base64, all data would be emitted unredacted to the audit log, and Transit, when performing a signing operation with a derived Ed25519 key, would emit public keys to the audit log. This issue has been patched in OpenBao 2.4.2.
