Is this an openssl base64 bug? With a particular message I don't get the correct size of the decoded message. The base64 encoded file itself looks good. Other tools than openssl does base64 decode correct.
cmdline example: openssl base64 -d -in text.pem -out text.der --> size of text.der = 5280 bytes instead of 5305 bytes When I insert at least one illegal base64 character somewhere in the base64 text (e.g. <SPACE> as first character in the file or insert an empty line somewhere in the base64 code) I'll get the correct decoded message (5305 versus 5280 bytes)! Does someone understand what's going on ...? Regards -- Beat On Thu, Jun 16, 2005 at 02:58:24PM +0200, Beat Jucker wrote: > When I try to decode a particular smime message I'll get error > "ASN1_get_object:too long". First I thought there's something > wrong with ASN.1 syntax but than I found a major difference > in openssl base64 decoding compared to other base64 tools. > > Given attached PEM file with all other base64 tools than > openssl (eg base64, mimencode, web online base64 decoder, > Asn1Editor, some kind of self written base64 test, etc) I'll > get a DER filesize of 5305 bytes with correct ASN.1 syntax. > > With all openssl versions I have tested (0.9.5...0.9.8) I'll > get a DER filesize of only 5280 bytes (openssl base64 -d). > This behavior is only on a very few smime files I recieve, > no problems on all other smime files. > > In my opinion there's something wrong with the PEM file. > I didn't write C code for a long time so I couldn't figure out > the reason why openssl stops decoding base64. > Any idea? > > Thanks > -- Beat
MIAGCSqGSIb3DQEHA6CAMIACAQAxggJgMIIBLAIBADCBlDCBjTELMAkGA1UEBhMCQ0gxDTALBgNV BAcTBEJlcm4xIDAeBgNVBAoTF0VpZGcuIE9iZXJ6b2xsZGlyZWt0aW9uMRUwEwYDVQQLEwxDQSBB YnRlaWx1bmcxDzANBgNVBAMTBk9aRCBDQTElMCMGCSqGSIb3DQEJARYWYWRtaW5AbTkwLmV6di5h ZG1pbi5jaAICA3MwDQYJKoZIhvcNAQEBBQAEgYAqrYhf0uTTTTOC2w45w8Pv1/xagYUuouk0w5n1 Pu3etMFoMpK8OkEdYB1Vuf1mcVQruMukWjF088OWPnuJca6S0xHAkJ/tRGur5udqbDcmZ2iJHUsd 5km0eNyFgPXHlREOOkX81z8xUw1zPSPWxjX5AtXOeImcv4Tmmw8UpvgF+TCCASwCAQAwgZQwgY0x CzAJBgNVBAYTAkNIMQ0wCwYDVQQHEwRCZXJuMSAwHgYDVQQKExdFaWRnLiBPYmVyem9sbGRpcmVr dGlvbjEVMBMGA1UECxMMQ0EgQWJ0ZWlsdW5nMQ8wDQYDVQQDEwZPWkQgQ0ExJTAjBgkqhkiG9w0B CQEWFmFkbWluQG05MC5lenYuYWRtaW4uY2gCAgNzMA0GCSqGSIb3DQEBAQUABIGAGD7PHuudx1Fz qUxb4L2f/nX90wkBXKfFO7S6/k1gZKLFVVNbSbOzUHVkG0nt6sJeNUZN4B4zbhdVG7VKvuBpQahD Bq1DNxDa8JrJLTgAYSlY2QRa2GmnUqL/aZGyB18rbRBMEqnLxzbxTZrf4B6pgSv/uWdxdHqhJePX BZwm8fAwgAYJKoZIhvcNAQcBMBoGCCqGSIb3DQMCMA4CAgCgBAi6od+OrqgzJaCABIIIAGKuU0DI sHlm8jxu/IfoEORdpCNm1O0Ng9LcVXr09bFd9T1eLmT9C30s4UXkTl7vNrsE/5aL4M+hVAD0uT3q 51wbnc02hxu+E5wKFM/V9GS6kJeAZjuWGchZzVsSpBIJLEv7EZ8FNiKRyEAhix1ZWwuk/YydKL+X lZeHuEYi2qFG1lmz0x8xGu+P7BJJMtgNhF8hWOmQPVTHGaTZrX9zTeMlC6dLc+jDgPycVqSRGCMX xq/Nx43wonxuCUIcYc3ArRoDDQ0g7yCCStmxgHjT7DJpLsK3Xf1J1rB/Td5TYGwUhKCoXudL4J3R ifkz+ePmpVU4MgGnQfEz/3/pdrohrEUbQuqLX0ysAbgLQ15tll6Y/PjClZXgwKC1CpzS4fm+7/um QneAP+SE0VNkooYxjCVNVfDM7MndkSROlrW6yqRXM61LkF8kps0NVKYmw4xBANuL4ourb76Wc/ns jEE6FJau3b8+FeWNFYvA8O5pkhsOYSidYiiS9EM6uGxuCBSufPZcz3M0rjv0YLIOyc1MuHekuKg9 Kwl0HxdgVjTNx7ziuXybnzmPRn86Z8BUqVj3+3yQRAkRZiXxLAoDbreZjD6QYDMc4u/Cw81qls8K sowvPG1N31LRbxQ7XJKB/AtL9OqnvqoYPVjs93qUcqv5PwbMurv0kCX9xyGL5Q3lX441QRgygEYd fpQ5oS1ARozO/wcOQEqSOJ5CgfyJVM6tev5DJycvKt7uJAmjanrU9wqT1sD3RzR4TM28nCPepfHG xQP0FVzMN+Lx0EmYp0nP315YdUuEo58dUTyscgSOQfFwxlFKea+6s0tDbvMWwtgz9589alLur3/i ZKGWx5Vc+X6HU4FYejLcfvjeeFV9/fKPb78ASP3loHEYLy9oDe5EAbUoAVnUbyiKC1agK9CVQZwY A2xWgsKoRO8BCOs0oKZs4JGfK9UVLYAtpgy/9zVZH6oG/rh2aVDrdZhup1Ay3IGYuDjGbnbRO00k FNYUZpQU2+TPIOgEYtP5AtmJ7U7iGA5cjuKxhlz5+f+RbcYdGOQO8Emf0dNK4XjY8N6iw4l9Ozds GNg4Nyow8mnIFlbHHFiNA/eTPJoCzH1fss4R9rSopWIU029n5qvAaQsMjcz5zGvzkDkySaeBU4CR MO01YnH4wqnGGCZKaL9fe25OEHAGT0SYrEpdD1tIU77M982RudP0gZRzOhsUGJDJSajL3w8eW3Bn sSv9HN/KhQaf7XHDrmZJNH7C2wi/iYaZwkl7XRdbh8izbKkHmabN+CYnd+RQeSJatkjN5NmlSRru U6bSWO0BswNsU5r1hmVEpYuM/OdY7eJSjMPJZQKdLYi0tnZce4tBib2mlKKujjF6GL+X5KEaXhuC hIKBkCY+mWIYoPmtAdqZtsYVxrDUHHBxRcevW5XLRY1E3mzU8d1KH4rdZ6V0aQhfAwjZs04EdCgK qv3ePu/v0bzOv//mAddd8FfKehiqXl+liNV8T5RM3+umWzHX5NK11yg6PeNKb1SS9zbEJR3sa4Ax jO5dcE6XwUzDmlfuEXR7L8yVGewksdMEaz+jzHCIFyiT+JeI1vHUoCRvNfGWhejsW+obJB4Q4j3I L3PdGuKLRuWbkSpmn3/kIDXSK/JW3oDb/r6fbFUX3PW7pgqnfqa6mIdVs71AplCz1Ym7IJy0vGA3 ltD/bxxWl9+rAG0NjRNb8EoTV238NE/YrSDrmdeDl3e+rcBPrrQenY/XCiheDTOF7k5eOnE8XCTP 5R3Y2ueGiFfCQQcAB0013k1c5SMByuZeR8fSdAU6aoSQoX4MZdGCtlx7hB4jwFMzae6ziUH2M/ep cRfy2zT0ks4sX0PTI55/J+pSIS/gS6nEYKyOKwihipLHZNggfdun9z3o5/q5HadIZHHnpRuv3G69 hRtSZdk5/sZw+P6k37+kq85JjMXXj2+A8E4jwbiQcusSTtIYTF9a7zBTDshEqFkq5X4zC2kVcwsl rel2T+KocyifRc+UwbtDoqiRsiOHf1PLk4GG7OSwgMsLt/lEj4TfjVGemdPVaJhXtsspTYpJxFwX ZkL8renasC6CvOLEgTLvB5NkCIeJzH5/sy5NKPT92ufKasIwUMkaM5/DBv7iCRhx43rh0BOPI+0p cLz4KJu/Y+pRHRY4/TtSmVsGVxv4vSZQwOsLltqcGtK70NLw6por6Z363rht4UEoDdfdvpuh+m4F GA0KWO38QoS1gNITo8rRHnjJyi9+OqYCxwcyL1/1raAHK3JPYIfFyVDO5tJRSGucnwn3jsvk42GM Um28CPY8Fh0TukQMqYWLheU9nlBNynZPhE3CjqIvaU21CBNWekpSleM6vgS26y/1vR8XfO+iOzUT ErTNufUlPbQCFBtsp1+5lCBJHx+cVIg+AltDM60DJ8US8U/GSwPGn6o8/KNrviPz4k1Irk9Om6Yy bHAwTMkGO/7LqkcIAAC0L2w3K0X5ndDre9M5UXZv/AKRP+du5eTwz3P1RtgMcGh7zS5IQJt0AN6R dv0ZSX1gwG05jP2dof1HHTJO5k0/IwAw8bxlTZQWHqfv5tP5OkerJBJHURvF3or5+JT4yPTq+Ej4 GPB9mqzA+USVDUqF9tqOJz9fUvbvuP+rQfOelz4AlPFtsWOqyfe2bFWidy32VBzwNCljnBw4GFJ/ O3fk2/F5rqXDdkVJVIg1O9l6N6aLwne9t/9Obkb9Je7WgkubIagsyqlIT5NT7xyhBIIIABh8+u0q Tmaf/KKAiTeQh3cKUCh2QOteeiQpYdCHwxV6GilwGUalfughWRaGxlMwTMgsJFuPVs2VPRXnBCJL h51zfGbRF6uCNKHOXRI4mnUuQAH+Lx+fetf4cu9UPqds0UWZ5vk4vTR8ifaa1PicwPzw3+R8g0pA iMz7kqdBLjx81zUmqASRWL+BKGc5NcGL/48c9FAHtTsre28yrDF2poOqCl4Oik87emhacWqus1aM qTSoyf6Nm1RQEkDNDE3IAutHJpGeELFnJgKmkJRwxkfYaRxSVcvMr38RYkyNYgPr13GCYdtXimGZ kz0zLFCZ313lFQR2Abb0bSpaGpcEowLZ6Zy5DJdQjGpR8YnD83aNsx3BJvnP0UuI/4wOTYu+bQ3e nJNz1+vdp+5E1NxxAE5HFgyRat9NHXSV2VdEN9/L82gYovZ1qK7SXwqhKpHkU9ffMRrZCIFh9sYY HRaPcV+ImkOYQOo7sNumkLHkSgUvq3MIeyZL4V56ueDp9j8yHb52y0qTw8mIOzhLAmt70BFvJYg1 jh8MQvTTQWdMptjT4sbM7/sBbR1TPCWBHEs+rAgBqY5+H38vsrw4IhS41Tcs6ITmBK1bm9qBhnc7 M1OJsNOux4Efv1SuQANeLh65gJ6/zdnti9X75MyvW9LWk+M5uKYUvowMxyJZKaJbOl/vd/UtAVPx wp65/OTGtxvFjrpqPBFC3ZGlymvSAg9/h2OTJN1J5n+SexNLT5JArD637aVCNek763ONEmaXI6vu Aiw7Ukzt2NFPn42EsjIWKH2RupC1kDKhEoC1JpHknmlEQSVybEaypV0+sOAmxgzmVO3OXHGqnn0L p9wcpDO9OZ5Kuav/TErlDFa/uKEaZnT3amNqZhamXisQ/EC1epcP1cz8+953bF+ZgXwU7Xg3aYgz aJAcEwPZMXam3lsLhmvflmX+stEf5g71sJjlWVVKcdRjatPM5qFEU9veh2BS2xX1jXL+a2wAfZ+e OR7i85W8eS2uaWK9VcplcKmfxd4xySWYqpBJXj7ob7xyPRuFgkzVrhT5guFCUZAGh+qtfRG1yVW2 FD2Gc/MtS4BP25mo62dtr7G4F/9cbd/DKscKmMb9mIbmzjP2pQ86/cz4cG/SVfiOAR0KwqK+b3kT PAsnomRsNlOhE0wLEzDY6MGvvG2HI9+N1z2bRJgNWgaNqUiOdPRFrUUEIU6hzQprAAHrQGj+jJpS 7tQ69+Xvix7FTLLlwC+leZL5CmhSTJg2Jpiph4q9t6BrdL0XPze7G7B8aAEarH+oqUnIu13JSDT0 CjNdEOKsl5rdAJFTtjVw+LbjW9HgnJBI4ap7U8asnqkAGXLWOnIe0Jhz9HmSC4FDY2wQsoJanC3w POGEOwZjIku9htXN9SRDdvrmMSYf1KBf21RBznjOHww2L3HRnBW/PkkvrZHc9oikAU/TPMzLfuhq UVOh0KwkAr0MkyJRF2+LOLa+beAIU9VdmkM+WoYozRO9/+u06ObY/c8hLYkMM0YqRBKtX8+XjWwp C9MFU7UXAYEFR7vgbQeMxFSWzQMFzuaKYJGpsl0dt7d+pDbT8q9bcTKuSc0IyuJxZT/KVKwoIhB6 /X8jLKzQiQXbx8vnXzfoO74rb3n7UWK5jqKHotxjPyNRXM7plx/Qr+gH8gMBkzFvR25x3LyvzjMI 9QcbwuwcXK++fWCeBiVFExVaC/SR938e1V+KWZIWW0PpgAsznYNCtPBXQR2fx0zLrMOH5SC4yAmV P/IUCLN0lSP+AcNhyZ9P2oN7joddQVQiygxMloAIKwyoFJtO4PGbMCrJZugbGz9CqBe1jMbwqFGI Kn4tqnbpaWEjNh6rCmKJlkxpT+vUE+RRl+fwj/RPUj9Tde4ODgralMHIypbWJLtwxD1+jpfbYOAu Ilb7lwXcfSTum9K7VfXRnK4ljApZ0n1wsbl2s/Pak6A/QC4jYxPoJkwWPVXx7HSxCB36Y4TZ+/uG ausLJLij0wcM7TJt7juOxYPMvscxfZ9um/ucphBw0uVrCsfh7TcogiTxpFS04KHU3bGOR9UHAbGY ng/wt0UP6XtZYE1idVErOw2zkYfSDDbbh3aVasxaW1uH7CEujinHG1Ws4K6e/miRe+wnBNbMHaon K/bYsuUU7Cg9KXbS7WbyS3nMMeCpgSzU0YBmJz4z3ABQB60mGXMqlKZWgP2MnCxVyLY0pmzWJOoF jFarR9olKIepHT5HOQOTyjGNXzcuKEToBFI53LUnfWrcm+VkBHgF3zpu2CuLuiWyJUvpHY4fKpix Tv1D/4zFo+TTImoGcYKJQrkGKGEY6yP7QowwLJjUpIcWLMVYXuZtY8vPa1PHcV4S9gl3al48Hars IGbj5ZbomOGaYpZpun7704y1GMync5RewY9KE1/UCUnaQHKIZp6JEO/1STRxYOXlwWKknqUFcCeI XiOlGPwLZUsX1rFln83v8B/TYwKGn00udpyBzIlF0Y4TkVOQjvVfSYMcyh8/GZ5fGj+AGVeZotni ZC+MUf8BvSB2NlergzgKDsfkU1eEfsR+SneEc0BtCDsGKVLq1HnsFdxhTqhz2rXXgMflOcyPjMIt KqIawkWGIlGPu8hbH1pTLwKZsdJfRZsDndQhZOkLJBdHbSfOn72TkUrTyGEngnciG2io9BM7NIbJ qxXvQPj7sxhUBR3dzff+AUg90cH2TOHFbJSaizMBae9kP4f2ALmXGZUjcVYokA4fBIICAHTnjjVU dozi0geE57atSfIBUlFdpPZ1p2XK1Qrua2Lhhk1WXYzfFj9ztNP+pDdmXStUuRS7xG5EflMDDm79 3pjRJwknJovFdr4Z1holIgcIrh+fioPrz8fQWrUNDnzoHa8drbhep3AC0BxFLQkFUHwGTae5BzqH srEHsLiu1oJry1+Q7krq2BAAAP/TsnpTrX7d8vlCSHOoBqlpvUo2vYZKXoqzCCX5BRg76FLbqZIP 0xE96gLqDqURxaAeQGiuNvoXosA04b+sM3yOniE7/Zf5HHEZRod0yizJ24VwzfbpRMfjG/IfzizN MTwRuKG+AR5eY+vxCeIWchHKbCviVfpIBjPKZGBjoNwk88E7Y77dxFYxiSorc2pQ8t+bQnt8Bfre PpYh/qlkupHwfMiYKsqHvY/oJL1Ca+AAyCxo9M45hLPdsbGlNP3qffM04+uh24nrutO11+BaDGed P8P0xTKN/E08rQFPhjq0jdZJTUXr4n8UEODu59NGTgppZOMk64aS92tQSuT0GMoQIi5CZPGil4rP uvT0SkMADJ7rpryP2DTQqfg5aO438x7PN2SRpz2aPY7mgO0apDjEawF+6R43f6Fq9I/MnsdWMUNZ DJRgzsdLlEPEbD4zad6vQ1a6aARd/SmUKlatBKu7eO2GTbk+lShU6ABmoSbEmXPZ0YVmAAAAAAAA AAAAAA==