120 lines
3.9 KiB
Python
Executable File
120 lines
3.9 KiB
Python
Executable File
#!/usr/bin/python3
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import argparse
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import email.parser
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import email.policy
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import os
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import psycopg2
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import psycopg2.extras as ppe
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components = {}
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EVIDENCE_MAX = 20
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def add_component(t, c):
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if t not in components:
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components[t] = []
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components[t].append(c)
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def add_message(msg):
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for h in msg.items():
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add_component(*h)
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if msg.is_multipart():
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for p in msg.get_payload():
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add_message(p)
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else:
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if msg.get_content_maintype() == "text":
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charset = msg.get_param("charset", "iso-8859-1")
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add_component(
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msg.get_content_subtype(),
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msg.get_payload(decode=True)
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.decode(charset, errors='replace'))
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def extract_features(msgid, verbose):
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db = psycopg2.connect("dbname=bayes")
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csr = db.cursor(cursor_factory=ppe.DictCursor)
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csr.execute(
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"""
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insert into messages(id, message_id)
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values(default, %s)
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returning id
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""",
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(msgid,))
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msg_pk = csr.fetchone()["id"]
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evidence = []
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for t in components:
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prev = {""}
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length = 1
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while prev:
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current = set()
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for c in components[t]:
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for o in range(0, len(c) - length + 1):
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f = c[o:o+length]
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fp = f[:-1]
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if fp in prev:
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current.add(f)
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# We keep only those as "prev" values which already existed
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# in the database
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prev = set()
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if current:
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q = "select * from features where type = %s and length = %s and feature in (" + ", ".join(("%s",) * len(current)) + ")"
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q += " order by interesting desc nulls last"
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csr.execute(q, (t, length, *current))
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for i, r in enumerate(csr):
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prev.add(r["feature"])
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if i < EVIDENCE_MAX and r["interesting"]:
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evidence.append(r)
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length += 1
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evidence = sorted(evidence, key=lambda x: -x["length"])
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evidence = sorted(evidence, key=lambda x: -x["interesting"])
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interesting_evidence = []
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seen = []
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for e in evidence:
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for s in seen:
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if e["type"] == s["type"] and (e["feature"] in s["feature"] or s["feature"] in e["feature"]):
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break
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else:
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interesting_evidence.append(e)
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seen.append(e)
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ln = len(e["feature"])
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if ln >= 6:
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seen.append({"type": e["type"], "feature": e["feature"][0 : ln // 3]})
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seen.append({"type": e["type"], "feature": e["feature"][ln // 3 : ln * 2 // 3]})
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seen.append({"type": e["type"], "feature": e["feature"][ln * 2 // 3 : ln]})
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if len(interesting_evidence) >= EVIDENCE_MAX:
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break
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p1 = 1
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p2 = 1
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for i in interesting_evidence:
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if verbose:
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print("#", i["spam_prob"], i["type"], i["length"], i["feature"], sep="\t")
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csr.execute(
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"insert into used_evidence(message, spam_prob, type, length, feature) values(%s, %s, %s, %s, %s)",
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(msg_pk, i["spam_prob"], i["type"], i["length"], i["feature"]))
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p1 *= i["spam_prob"]
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p2 *= 1 - i["spam_prob"]
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p = p1 / (p1 + p2)
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csr.execute("update messages set type=%s where id = %s", ("%.6f" % p, msg_pk))
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db.commit()
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return p
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument('--verbose', action='store_true')
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ap.add_argument('file', nargs='?')
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args = ap.parse_args()
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if args.file:
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fh = open(args.file, "rb")
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else:
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fh = os.fdopen(0, "rb")
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parser = email.parser.BytesParser(policy=email.policy.default)
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msg = parser.parse(fh)
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add_message(msg)
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p = extract_features(msg["Message-Id"], args.verbose)
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print(p, "spam" if p > 0.5 else "ham")
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main()
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